Bitcoin Protocol: Model of ‘Cryptographic Proof’ Based
Global Crypto-Currency & Electronic Payments System
Yogesh Malhotra, PhD

Future of Finance Project (, Global Risk Management Network, LLC,
757 Warren Road, Cornell Business and Technology Park, Ithaca, NY 14852-4892, U.S.A.

"Bitcoin price volatility implies huge market risk." - Economist Nouriel Roubini
- Roubini launches stinging attack on bitcoin, CNBC, March 10, 2014.

December 04, 2013

This research report represents the first known attempt with specific technical focus on cryptographic ‘proof of work’ in the context of virtual crypto-currencies such as Bitcoin. The cryptography, encryption and cryptanalysis technical focus of the report is intentional and related to Bitcoin’s innovative capabilities, vulnerabilities and threats. Money is an interesting construct that continues to occupy the fancy of many ranging from economists to quantum physicists... The future of money becomes "entangled" with future of money laundering when focus is not on privacy and anonymity alone, but also lack of traceability... Situated somewhere along the trajectory between real money and quantum money, virtual crypto-currencies based upon ‘cryptographic proof’ represent a natural stage in the evolution of global finance... The future of money, whatever form it may take – virtual or quantum, will quite likely be "entangled" with the future evolution of ‘cryptographic proof of work.’ The feasibility and large-scale global implementation of Bitcoin as a crypto-currency has earned it admiration as a remarkable conceptual and technical achievement and an elegant solution. Its cryptographic solution enables creation and regulation of issue of crypto-currency, preventing its counterfeiting and double-spending, and securing its global transmission at minimal transaction cost while using little time. Central to all those interesting innovations is the cryptographic ‘proof of work’ supplanting trust in a third-party that is the central focus of the current study.

“The bitcoin protocol provides an elegant solution to the problem of creating a digital currency—i.e., how to regulate its issue, defeat counterfeiting and double-spending, and ensure that it can be conveyed safely—without relying on a single authority... It represents a remarkable conceptual and technical achievement, which may well be used by existing financial institutions (which could issue their own bitcoins) or even by governments themselves.”
-- The Federal Reserve Bank of Chicago, Chicago Fed Letter, December 2013, No. 317

Bitcoin Protocol: Model of ‘Cryptographic Proof’ Based
Global Crypto-Currency & Electronic Payments System


"For the importance of money essentially flows from its being a link between the present and the future."
-- The General Theory of Employment, Interest, and Money, John Maynard Keynes, 1935

"You can know the name of a bird in all the languages of the world, but when you're finished, you'll know absolutely nothing whatever about the bird... So let's look at the bird and see what it's doing -- that's what counts."
-- "What is Science?" The Physics Teacher, 1969, Richard P. Feynman

Money is an interesting construct that continues to occupy the fancy of many ranging from economists to quantum physicists. Virtual crypto-currencies enabled by global interconnectivity and ‘cryptographic proof of work’ represent a natural stage in the evolution of virtual global financial transactions and exchange. Bitcoin is one such crypto-currency that seems to be a ‘remarkable conceptual and technical achievement’ and ‘an elegant solution’ to creating a digital currency, regulating its issue, countering counterfeiting and double-spending, and ensuring secure transmission without relying on a single authority. Central to the interesting innovation is the cryptographic ‘proof of work’ that supplants trust in any third-party in enabling exchange of value. This research report is the first known attempt to specifically focus on cryptographic ‘proof of work’ in the context of Bitcoin and how it really works in enabling Bitcoin’s innovative capabilities. It also analyzes the mystery shrouding Bitcoin’s origin trying to examine if it is a cryptographic protocol, virtual currency, financial instrument, or something else. Central focus is on Bitcoin’s cryptographic proof based P2P electronic payment system with focus on Bitcoin addresses and public key cryptography, transactions and ECDSA-based digital signatures, time-stamping and organizations of transactions into blocks, and mining of cryptographic proof to create the transaction block chain and enable trust. Some perspective of the multi-billion dollar ‘Bitcoin economy’ is also provided in the context of analysis of Bitcoin mining and cryptographic proof computing power requirements. Potential weaknesses in Bitcoin’s security and encryption protocols and recently highlighted key security vulnerabilities and attacks including lack of perceived user identification anonymity are discussed.

Introduction: Virtual Currency:  Beginning of the End of Real Money?

The IEEE Spectrum special report Future of Money heralding ‘The Beginning of The End of Cash’ chronicles growing trend of virtual currency transactions. It outlines growing use of centralized and decentralized digital cash such as Bitcoin. Beyond virtual currencies, it discusses how quantum computing developments will enable quantum money, i.e., real money which cannot be counterfeited. The future of money becomes "entangled" with future of money laundering when focus is not on privacy and anonymity alone, but also lack of traceability. For instance, the above report notes that: “Anarchists, drug dealers, prostitutes, politicians, dog walkers, and nannies all have reason to prefer cash. There’s a big, spinning world of under-the-table transactions, and what makes it go round is cash." Based on 20% improperly reported or unreported US income, US Treasury lost half-trillion dollars in 2008 alone. Bitcoin is of particular interest given “it is truly untraceable and therefore, like cash, cannot be recovered if lost or destroyed.” Bitcoin extensions such as Zerocoin by a Johns Hopkins computer scientist are further expected to emulate truly anonymous and untraceable money laundering pools.

Virtual Currency and the Emergence of Bitcoin Crypto-Currency

Bitcoin is called a crypto-currency as it relies on cryptography to generate the ‘currency’ and validate related transactions. The real pursuit of virtual currency began around early-1990s among individuals concerned about privacy, anonymity, and lack of traceability. Among them was a group of Silicon Valley friends who fancied liberating currency from governmental control. Around same time, a computer scientist named Nick Szabo was contemplating ‘bit gold’ as a digital coin given as reward for solving difficult-to-solve problems. His scheme of ‘miners’ of coins dedicating CPU-power to solve system-assigned cryptographic equations seems a likely precursor to later Bitcoin. Like Bitcoin, he also envisaged solving problems as cryptographic proof-of-work (PoW) that is approved by the network and becomes part of the next system-assigned challenge. 10-15 years later, the Bitcoin paper by unknown “Satoshi Nakamoto” contemplated creating similar ‘chain of data’ as a record of block chain of transactions.

Bitcoins: Virtual Currency, Financial Instrument, or ‘Something Else’?

US Senate Committee on Homeland Security and Governmental Affairs recently conducted a live hearing on virtual currencies with primary focus being on Bitcoin. In online archive of testimony statements is the original Bitcoin paper which is at the crux of the whole affair. Presented as the central piece of the testimony hearings, interestingly, it is authored by someone who evidently doesn’t even exist. First appearing online in November 2008 it was followed by the Bitcoin network in April 2009. Debate is on among worldwide governments about how to regulate Bitcoin: as currency or financial instrument as it defies most such comparisons given its notorious uses as well as price-volume behaviors. Germany recognized it as a ‘financial instrument’ unlike e-money or foreign currency. US Department of Homeland Security earlier closed US bank accounts of Mt. Gox, the world’s largest bitcoin exchange until a month ago. In US Senate hearing testimony, Fed Chairman Ben Bernanke observed that such virtual currency exchanges and related bank transactions must comply with Bank Secrecy Act (BSA) and Anti-Money Laundering (AML) requirements. He also reinforced Fed’s role in enforcement of section 311 of US Patriot Act against Bitcoin exchanges such as Liberty Reserve S.A. which pleaded guilty in a $6 billion money-laundering case.

Having earlier outlawed virtual currencies, China recently allowed popular participation in Bitcoin market while emphasizing that it does not recognize Bitcoin. With China now accounting for 62% of the global market volumes in Bitcoin, its move is attributed to the BTC price crossing the $1,000 mark for the first time and BTCChina is now the world’s largest Bitcoin exchange. Related concern is that Bitcoin can threaten US dollar’s status as world’s reserve currency with yuan-Bitcoin exchange rate now becoming a leading indicator of the dollar-Bitcoin rate. With $8 billion worth of US residential real estate purchased over last year, wealthy Chinese share of foreign US residential real estate has jumped 50%. Chinese now own between $450 billion to $700 billion in offshore assets, with most wealth transferred illegally such as by using BTC as legally each of them can’t transfer more than $50,000. Rising 7,600% over the year and on track to being world’s first trillion dollar non-fiat ‘currency’, BTC rose to $1,175.79 on Nov. 28, 2013, as shown in Figure 1. In response, most of Canada’s Big-6 banks froze or shut down the accounts of exchanges that convert BTC to cash for customers.

Figure1. Astronomical Rise of the BTC, data source:

The pseudonymous Satoshi Nakamoto is characterized as the ‘inventor’ of Bitcoin. Various firms (Samsung, Toshiba, Nakamichi & Motorola as in SaToshi NakaMoto), and institutions such as the NSA (Nakamoto, SAtoshi) are identified among entities that may have ‘invented’ Bitcoin using the pseudonym. Some note similarity of pseudonym with Tatsuaki Okamoto, cited among references in the 1996 paper How to Make a Mint: The Cryptography of Anonymous Electronic Cash authored by National Security Agency’s Office of Information Security Research and Technology Cryptology Division. Twelve years before the Bitcoin paper, the NSA paper, based upon its review of electronic cash schemes, made notable observations. It noted that cryptography underlying those schemes seemed fine and delivered promised anonymity. It also observed however that those schemes seemed not as satisfactory from a law enforcement point of view: “In particular, the dangers of money laundering and counterfeiting are potentially far more serious than with paper cash. These problems exist in any electronic payment system, but they are made much worse by the presence of anonymity. Indeed, the widespread use of electronic cash would increase the vulnerability of the national financial system to Information Warfare attacks.”

Some reports note the first creation of BTC on January 3, 2009 as ‘all bit and no coin’ based upon ‘thirty-one thousand lines of code and an announcement on the Internet’. Over two years, the mysterious pseudonymous inventor is said to have written hundreds of posts in flawless English inviting other developers to improve the code. In April, 2011 he is said to have been heard from last when he sent a note to one of them that he has moved on. First Bitcoin to U.S. dollar exchange transaction in history, 5,000 BTC for $5 on PayPal, is self-attributed by Finnish developer Martti Malmi. BTC at less than a penny initially rose above $29 by June 2011 falling to $5 by September 2011. It crossed $100 between April and May 2013 and $200 around October 21, 2013. In the week before the US Senate Hearing, it crossed $400 and shot past $900 on the day of Hearing before diving back to around $500. Based on a report that estimated Nakamoto’s million BTC holding at $100 million in first week of May, 2013, he may have cashed out as a billionaire on the day of Senate Hearing. Analysts are bewildered as the price volume action begs answers to questions such as: What other ‘currency’ or ‘financial instrument’, if any, demonstrates such price-volume behavior? What are the fundamentals, if any at all, that provide any realistic assessment of the true valuation of a BTC?

Besides world’s largest multi-billion dollar money-laundering case, Bitcoin has been linked with multiple other criminal activities such as child pornography, bank hacking, and sale of prohibited drugs. On the day of US Senate Hearing, Forbes published about the online service Assassination Market for crowdfunding political assassinations of any government official by collecting anonymous BTC contributions. On other hand, Bitcoin cryptographic P2P digital system enables near instantaneous global payment transfers for minimal transaction fees making it appealing to consumers, speculators, and cybercriminals. Bitcoin identifies individual users by “addresses” that are ‘plausibly deniable’, i.e., a merchant receiving BTCs as payments may not deliver on promised services and yet the payments are not reversible. Extensions of Bitcoin such as Zerocoin are further expected to enable truly untraceable money laundering pools.

Bitcoin: A ‘Cryptographic Proof’ Based P2P Electronic Payment System

Bitcoin, a cryptographically secure decentralized peer-to-peer (P2P) electronic payment system enables transactions involving virtual currency in the form of digital tokens. Such digital tokens, Bitcoin coins (BTCs), are a type of crypto-currency whose implementation relies on cryptography to generate the tokens as well as validate related transactions. Bitcoin solves counterfeiting and double-spending problems without any centralized authority. It replaces trust in a third-party such as a bank with a cryptographic proof using a public digital ledger accessible to all network nodes in which all BTC balances and transactions are announced, agreed upon, and recorded. Transactions are time-stamped by hashing them into an ongoing chain of hash-based PoW forming a record that can’t be changed without redoing that chain. Anonymity is maintained through public-key cryptography by using P2P addresses without revealing user identity.

Bitcoin Addresses & Public Key Cryptography

Bitcoin coin (BTC) is essentially a hashed chain of digital signatures based upon asymmetric or public key cryptography. Each participating Bitcoin address in the P2P network is associated with a matching public key and private key wherein a message signed by private key can be verified by others using the matching public key. A Bitcoin address corresponds to the public key which is a string of 27-34 alphanumeric characters such as:


and occupies about 500 bytes. Users are encouraged to create a new address for every transaction to increase privacy for both sender and receiver. While this creates anonymity for both sender and receiver, however, given irreversibility of transactions, nonrepudiation may be compromised. Addresses can be created using Bitcoin clients or ‘wallets’. The sender uses his or her private key to assign payments to receiver’s public key oraddress. Characters within the address also serve as checksum to validate any typographical errors in typing the address. The private key is the secret key which is necessary to access BTCs assigned to the corresponding public key address. Private keys start with first character 1 or 3: 1 implies use of one key while 3 denotes multiple private keys for ‘unlocking’ a payment. Bitcoin addresses and associated private keys are stored in encrypted wallet data files typically backed up offline for security. If a wallet or a private key is lost, related BTCs are lost forever.

Bitcoin Transactions & Digital Signatures Based on ECDSA

Bitcoin’s operation is based upon elliptic curve cryptography: addresses are derived from elliptic-curve public keys and transactions authenticated using digital signatures. Elliptic Curve Digital Signature Algorithm or ECDSA is the cryptographic algorithm used by Bitcoin to ensure that funds are spent by rightful owners. The private key, a single unsigned 256 bit integer of 32 bytes, is essentially a randomly generated ‘secret’ number supposedly known only to the person that generated it. The range of valid private keys is governed by the secp256k1 ECDSA standard used by Bitcoin. The public key corresponds to a private key, but does not need to be kept secret.

Figure2. How Bitcoin Addresses Transfer Payments and Verify Signatures

A public key can be computed from a private key, but it is presumably computationally infeasible to do vice-versa. A public key can be used to authenticate or confirm the validity of the digital signature. As shown in Figure 2 above, address N transfers the payment to address M by digitally signing using its private key the mathematically generated hash H of prior transaction TN and public key of address M. Also, as shown, the digital signature of address N can be verified by using N’s public key without knowing its private key. The Bitcoin block chain contains all such transactions ever executed wherein each block contains the SHA-256 hash of the previous block.

The elliptic curve over a finite field Fp, with most popular choice being prime fields GF(p) where all arithmetic is performed modulo a prime p, is set of all pairs (x, y) ∈ Fp which fulfill E:

            y2x3 + a.x + b mod p

together with an imaginary point of infinity O , where p > 3 is prime, and a, b ∈Fp. The cryptographic signatures used in Bitcoin are ECDSA signatures and use the curve secp256k1 defined over Fp where p = 2256– 232– 977 which has a 256-bit prime order. This choice deviates from NIST recommended FIPS 186-4 standard in that the curve coefficients are different from the NIST recommended standard to speed up scalar multiplication as well as Pollard’s rho algorithm for computing discrete logarithms.

Given ECDSA public-key K, Bitcoin address is generated using the cryptographic hash functions SHA-256 and RIPEMD-160:

HASH160 = RIPEMD-160(SHA-256(K)).

Bitcoin address is computed directly from the HASH160 value as illustrated below in Figure 3, where base58 is a binary-to-text encoding scheme:
Figure3. How Bitcoin Address is Computed Using ECDSA Algorithm

In summary, the electronic coin, BTC, a chain of ECDSA enabled hashed digital signatures, is transferred by the sender (payer) who appends to it a digitally signed hash of previous transaction and the public key of the receiver (payee). The receiver relies upon signatures to verify the chain of ownership and on P2P majority consensus about the single history of order in which publicly announced transactions are received.

However, Bitcoin ECDSA signatures may be susceptible to the following potential encryption related vulnerabilities and threats: (i) insufficient or poor randomness when the same public key is used for multiple Bitcoin transactions or the same key pair is used to protect different servers owned by the same entity; (ii) an invalid-curve attack in which an attacker obtains multiples with secret scalars of a point on the quadratic twist, e.g. via fault injection if the point doesn’t satisfy the correct curve equation (iii) implementation issues such as side-channel attacks, software bugs, design or implementation flaws; (iv) hardness assumptions about number theoretic problems such as integer factorization and discrete logarithms computation in finite fields or in groups of points on an elliptic curve not applying as assumed in specific contexts. Recent recommendations by RSA, about withholding use of Dual Elliptic Curve Deterministic Random Bit Generation (or Dual EC DRBG) and the influence of DRBG compromise on consuming applications such as DSA may also deserve attention.

Organizing Transactions into Blocks and Time Stamping Them

A BTC transaction is a signed section of data broadcast to the network and collected into blocks. It typically references prior transaction(s) and assigns specific number of bitcoins from it to one or more Bitcoin addresses. Transactions are recorded in the network in form of files called blocks. Structures of the blockheader and block are shown below.
Figure4. Structure of a Bitcoin Transaction Block
Figure5. Structure of a Bitcoin Transaction Blockheader

As seen in Figures 4 and 5, a block contains most recent transactions sent to the network not yet recorded in prior blocks. Each block includes in its block header a record of some or all recent transactions and a reference to the prior block. It also contains the ‘answer’ to a difficult-to-solve mathematical problem related to the verification of transactions for the block. This problem relates to finding factors of a very large integer: difficult to solve but thereafter easy to verify by other nodes once factors are found.

The chain of ownership is created by using a timestamp server that creates and widely publishes hash of a block of items to be time-stamped with each timestamp including previous timestamps in its hash value. To prevent double-spending, i.e., ensuring that the BTC payer didn’t sign an earlier transaction for same BTC or already spent the BTC, a timestamp server is used to maintain a single chronological history in which each transaction was received. This process ensures that at the time of the transaction, the payee knows that majority of nodes agree to having received the current transaction as the first received. Subsequent transactions for the same BTC don’t need to be recorded as they are rejected in the verification process. As the only way to confirm absence of a transaction is to maintain a record of all transactions, as seen in Figure 6, each timestamp includes the previous timestamp in its hash starting from first transaction.
Figure6. Each Timestamp Includes Previous Timestamp in its Hash Forming a Chain

The block chain makes double-spending very difficult as each block is preceded by prior block in chronological order as well as is based upon its hash value. To prevent double-spending, i.e., spending of the same BTC twice, public keys and signatures are published as part of publicly available and auditable block chain. To make it infeasible to falsify the block-chain, PoW is used to make addition of each block very costly.

Mining Cryptographic Proof of Work to Create Transaction Block Chain

Transactions are bundled into blocks by network nodes functioning as miners. Mining is the process of attempting to generate validation hashes, i.e., competing to be the first to find and broadcast the correct hash based upon large integer factorization that ‘solves’ the current block. A block chain is a transaction database shared by all nodes in the network and contains every executed transaction. Every block in the chain contains a hash of previous block thus creating a block chain from the first block to the current block. A block chain may be searched or navigated by using a block chain browser.

BTCs acquire perceived value based upon PoW in terms of computational power invested for solving the cryptographic challenge of prime factorization of large numbers related to verification of BTC transactions. BitCoin uses SHA-256 hash algorithm to produce verifiably large random numbers requiring predictable amount of CPU power to factorize. Generating a SHA-256 hash with value less than the current target, a 256-bit large number that all Bitcoin clients share, solves a block which ‘mines’ new coins that the responsible miner receives as incentive for solving the problem.

The P2P distributed timestamp server is implemented using PoW by incrementing a nonce in the block until its hash results in required zero bits beginning the hash. As depicted in Figure 7, to create different cryptographic hash values from the same input string, mining computers calculate cryptographic hash values based on combination of hash value of all prior Bitcoin transactions, the new transaction block, and a nonce.
Figure7. Mining Cryptographic Proof of Work to Create Transaction Block Chain

The nonce in a bitcoin block is a 32-bit (4-byte) field, its value is set so that the hash of the block will contain a run of zeros. According to NIST SP800-90A, nonce is a time-varying value that has at most a negligible chance of repeating, for example, a random value that is generated anew for each use, a timestamp, a sequence number, or some combination of these. (DRBG uses a DRBG mechanism and a source of entropy input, and may, depending on implementation of DRBG mechanism, include a nonce source.)

Any change to block data such as changing nonce results in totally different new block hash value. It is infeasible to predict which initial data set will create the right hash with the required number of leading zeros. Hence, miners need to generate many hashes with different nonces until they can find one that works. Iterative computation requires time and resources; hence presentation of the block with correct nonce value constitutes the PoW. Double-spending same BTC would require not only re-computing and replacing the transaction where it was spent but also all subsequent blocks in the chain. This characteristic underlies the use of the longest block chain as the most reliable and trusted PoW by all nodes as well as apparent infeasibility of re-computing the same block chain to falsify it such as in order to reverse a transaction. Hence the longest block chain verified and included in most recent hashed output of the public ledger accessible to all P2P nodes serves both as the purveyor of ‘cryptographic trust’ as well as the deterrent of reversibility of transactions.  

SHA-256, a member of the SHA-2 algorithms designed by the NSA and extensively used in Bitcoin protocols, is based on the following cryptographic hash function, majority function, and circular (modular) rotations and shifts.

SHA 256 is known to be potentially vulnerable to collisions besides pre-image attacks, non-linear reduced round attacks, and higher-order differential attacks. Similarly, RIPEMD-160 is potentially susceptible to differential attacks, pre-image attacks and collision attacks. As SHA-2 shares same structure and mathematical operations as already “broken” SHA-1 and MD5, this is a cause for concern. To replace SHA-2 in case of a cryptanalysis attack that weakens it, SHA-3 is the new cryptographic hash algorithm selected by NIST. SHA-3 has fundamentally different structures and uses quite different mathematical operations as compared with SHA-2. Additional concerns relate to current publicly known classical computers capable of 54.9-petaflops and quantumcomputers in use for heavy-duty benchmarking by Google, NASA and others which may have additional implications about potential vulnerabilities.

Summary: How Bitcoin P2P Electronic Payment System Works

The Bitcoin P2P network protocol thus works in an approximately step-by-step fashion as envisioned by its original pseudonymous inventor in the historic proposal.

  1. New transactions are broadcast to all nodes.
  2. Transactions into a block by each node...
  3. …Which then works on finding a difficult proof-of-work for its block.
  4. When a proof-of-work is found, the node broadcasts the block to all other nodes.
  5. Nodes accept the block and its transactions only if valid and not double spent.
  6. Nodes accept the block by starting creating next block in the chain while using hash of accepted block as previous hash.

Mining & Cryptographic Proof Computing Power Requirements

After about every 10 minutes, miners bundle payment transactions into blocks which are subsequently included in the shared ledger i.e. longest block chain of balances and transactions. In the Bitcoin protocol, new BTCs are generated as incentives to reward miners for verifying transactions and creating cryptographic proof that replaces trust in a third party such as a bank in case of real cash exchange. Prior discussion on the ‘Proof of Work’ and hashed block chains focused on the technical details of the cryptography and security encryption protocols. Related computational resource requirements and the actual process of increasingly specialized mining given exponentially growing difficulty and exponentially decreasing [potential] of reward seem equally interesting.

The computationally challenging problem that miners solve is focused on factorization of large primes and is associated with verification of transactions discussed above. Assuming new transaction block NB is to be added to existing block chain BC, then miners need to find nonce N which will result in the hash F(BC, NB, N) that starts with the required number of zeros as well as is smaller than the current target T specified by the system at that time. As well recognized in cryptanalysis research about prime factorization of large numbers, while finding such factors is computationally complex, verifying their product is not difficult. Also, lower the value of T, the more computationally challenging is the factorization problem. Rate of increase in the computational complexity grows exponentially so that mining of new coins decreases exponentially getting halved in every subsequent year so that there will be only a total of 21 million BTCs by 2040. Given exponentially increasing complexity, miners have already advanced beyond specialized hardware such as specialized Bitcoin mining ASICs clocking billions of hashes per second to pooled resources such as botnets.

Exponential computational difficulty can be checked using a Bitcoin mining profitability calculator which lists current difficulty level at: 707,408,283 and current incentive at 25 BTC per block. Difficulty is defined here as a measure of how difficult it is to find a new block compared to the easiest it can ever be. It is adjusted every 2016 blocks based on the time it took to find previous 2016 blocks. At the desired rate of one block each 10 minutes, 2016 blocks would take exactly two weeks to find regardless of the exploding number of participants in the P2P network that make the ‘game’ even more challenging. Even after doing all the hard work, there is no guarantee that you have made any progress: “There's no such thing as progressing 1% towards the solution as at every point, the probability is same. After working on it for 24 hours, your chances of solving it are equal to what your chances were at the start or at any moment. Believing otherwise is what's known as the gambler's fallacy.” For those venturesome to go solo BTC mining with an average desktop, a rough estimate of ‘Net Profit of -1464.60 USD’ is available at the time of writing from as shown in Figure 8.
Figure8. BTC Mining Has Become a Deep Pocketed 'Pooled Player' Game

As mentioned, mining has advanced way beyond CPUs (central processing units) to GPUs (graphics processing units) to more flexible FPGAs (field-programmable gate arrays) to bespoke ASICs (application-specific integrated circuits). Mining groups now pool processing power using server farms with arrays of racks of ASIC cards dedicated to mining. For any new block created by hashing old transaction block, the first transaction originally created 50 BTC reward for the block creator. Algorithmically, the reward is set at 50 BTC from 2009 to 2012, 25 BTC from 2012 until late 2016, and so forth so that there will never be more than 21 million BTCs. Once BTC mining is exhausted, transaction fees paid to miners are expected to constitute the difference between a [higher] input and [smaller] output of BTCs. With latest specialized hardware, mining has reached a point where only those with access to free or cheap electric power can afford to continue and even they will produce a relatively marginal return on investment.

Increasing computational complexity of mining is also evident in the following charts for network hashing (Figure 9) and Bitcoin daily growth (Figure 10) rates from More nodes, or specifically, more CPU power, involved in mining makes it all the more harder to generate SHA-256 hashes which need to be generated by brute force of computing power.  
Figure9(a). Exponentially Growing Bitcoin Total Network Hashing Rate  
Figure9(b). Exponentially Growing Bitcoin Total Computation Speed  
Figure10. Bitcoin Daily Growth Rate

With many online websites and services dedicated to tracking BTC markets and transactions, a quick snapshot of the ‘BTC Economy’ from one such site is shown in Figure 11. Some interesting numbers from those statistics include: current total 12,061,150 BTCs with market cap 12,248,339,048 USD, 8.29 blocks generated per hour, and network hashrate of 66840.80 PetaFLOPS. Also, it is clear that BTCChina is the predominant BTC exchange leader after overtaking lead from Mt. Gox.
Figure11. The 'Bitcoin Economy' Overview Snapshot

Cryptographic Proof as Substitute for Trust in Third Party

When a miner finds a suitable block hash, he couples it with a nonce and broadcasts it to the network. Resulting hash is combined with previous completed block hash along with the BTCs being exchanged thus forming the block chain. The block chain represents the ‘trust’ of each transaction because each new transaction block is generated based on the unique hash of the previous block of all prior transactions. The entire history of every transaction can be traced back through the longest chain that is ‘trusted’ by all P2P nodes which keep extending it further. Because the network trusts the longest continuous block chain and a suitable SHA-256 hash may take 10 minutes or so to generate, an attack would require more computational power than all honest nodes combined. To pre-empt such possibility, a block is not considered final until it is 6 links deep which may take up to an hour. The distributed timestamp server generates proof of chronological order of transactions and the system is supposed to be secure unless a group of attacker nodes can collectively control more CPU power than honest nodes.

Known and Potential Attacks and Vulnerabilities of Bitcoin

Pros and cons of Bitcoin as well as potential weaknesses in its security and encryption protocols were discussed above; other potential vulnerabilities are summarized below.  Most probably, the pseudonymous Bitcoin inventor didn’t envision today’s global BTC mining computational arms-race with armies of botnets using global captive computers, software vendors using malware to steal customers’ CPU power for mining BTCs, or clearly illegal service using ransom-ware forcing law enforcement officers into making BTC payments via their openly public customer service Web site.

Bitcoin is known for its [pseudo-]anonymity of user identification as it uses randomly generated public keys for Bitcoin addresses; however, it is not truly anonymous. As noted in the US Senate Hearing testimony of the Criminal Division: “Criminals are drawn to services that allow users to conduct financial transactions while remaining largely anonymous… [However,] To be clear, virtual currency is not necessarily synonymous with anonymity.” Public key addresses are self-identified by users for receiving payments or when they need to convert BTCs to other currencies including real money when user identity is linked with related public key address. Furthermore, different public keys that are input in a specific transaction or a sequence of transactions can be related to the specific users and the private keys used for sending payments need to be known to the transmitting exchanges. Also, change addresses used for returning residual ‘change’ from Bitcoin transactions can be linked to respective input addresses as well as input users. Private transactions between parties of same exchange are privy to the exchange which may be able to bypass such identification by not using the strict Bitcoin protocol of transparency of each transaction. The ‘default’ Bitcoin protocol doesn’t provide true anonymity which may require protection from both forward attacks and reverse attacks. Forward attacks involve getting something that identifies a user using coins received with methods that should remain secret. Reverse attacks involve getting something that should remain secret by using coins that can identify a user.

Several additional ‘weaknesses’ representing vulnerability of Bitcoin coins and transactions are identified next. Wallet files are vulnerable to theft and need to be encrypted and backed off-line. Old backup wallet files and contents can be retrieved with existing backup facilities. Coin’s history can be traced to link user identities to the pseudo-anonymous addresses. Unlike Bitcoin addresses, if a payment is sent to IP address, man-in-the-middle attack is feasible given IP addresses can be spoofed. Unless node-to-node encryption is used, packet sniffing can reveal the sent transactions. Distributed denial of service (DDoS) attacks pose potential threats just like with any other networked cryptographic service. However, deep-pocketed DDoS attacks using ‘remarkable 100 G/bits per second in bandwidth’ and million-dollar hacking heists are becoming increasingly common. Timejacking attacks can be done by announcing inaccurate timestamps when connecting to a node where an attacker can deceive it into accepting an alternate block chain by altering the node's network time counter. Results may range between increased chances of double-spending, drained computational resources, and slower transaction rates. Potential causes for concern for miners also include: more efficient mining gear only raises the network ‘difficulty’ without reducing energy use and cheaper energy linearly increases mining energy use. Similar concerns apply to other cryptographic proof of work currencies such as Litecoin as well.

Besides vulnerabilities of encryption protocols to available quantum computers, classical computers capable of 54.9-petaflops may pose major ‘>50%’ threat to Bitcoin. The specific attack results from anyone in the network acquiring more than 50% computing power being able to exclude, modify, and self-reverse transactions and prevent some or all ‘mining’ of valid blocks. Even with less than 50% power such attacks are feasible: e.g. someone with 40% of network computing power can overcome a 6-deep confirmed transaction with a 50% success rate. Nevertheless, it is exponentially difficult to change historical blocks going back in time and it isn’t possible to change blocks created before the last checkpoint. Even though a profit-seeking attacker potentially may gain from following the protocol or launching other attacks, however, “if the above attack is successfully executed, it will be difficult or impossible to "untangle" the mess created -- any changes the attacker makes might become permanent.” Given individual mining pools have controlled 25% to 33% of mining power, a Cornell study, argues that >50% attack is feasible even though developers seem not as concerned.

Double spending attacks to which the Bitcoin protocol is vulnerable include Race attack, Finney attack, Vector76 attack, Brute force attack, and >50% attack. The research study Two Bitcoins at the Price of One found that the Bitcoin protocol is highly susceptible to Race attacks. Such attacks involve successfully sending one transaction to a merchant while sending different transaction spending same coins that were first sent to eventually make it into the block chain. The Finney attack is another fraudulent attack requiring the miner’s participation once a block has been mined with a conflicting transaction not yet announced to the network. While a miner verifying the block that contains money sent by someone to oneself, the sender may find the block and send the money to someone else. The sender receives his money while the legitimate transaction is rejected as the same money can’t be double spent. Vector76 attack is a combination of the above two attacks such that a transaction that even has one confirmation can still be double-spent. In a Brute force attack, the attacker submits to the merchant or network a transaction which pays the merchant, while privately mining a blockchain fork in which a double-spending transaction is included instead. In >50% attack discussed earlier, the attacker simply perseveres with private fork generating blocks faster than the rest of the network until he controls the longest branch superseding those of the honest network.

Future of Bitcoin and Other Crypto-Currencies

In his letter of September 06, 2013, the Chairman of the US Federal Reserve, quoting a 1995 US House of Representatives hearing, noted that: “while [virtual currency] innovations may pose risks related to law enforcement and supervisory matters, there are also areas in which they may hold long-term promise, particularly if the innovations promote a faster, more secure and more efficient payment system.” In many ways, despite their notorious widespread use in illegal activities the current popular appeal of crypto-currencies such as Bitcoin seems to stem from the innovations that the Fed Chairman and the Chicago Fed mentioned in their respective documents. In his letter, the Fed Chairman underscored the need for regulatory compliance on part of public and private players in electronic cash and related banking and finance industries. On the other hand, there is the search for true anonymity and privacy on part of some academics and practitioners besides users of such crypto-currencies as discussed. The future of cryptography, cryptanalysis, and crypto-currencies is anticipated to evolve based upon reconciliation of expectations, needs, and wants of diverse stakeholders.

A snapshot of the current contenders for that future of crypto-currencies is displayed in this concluding discussion. Currently, there are 30 to 40 virtual currencies listed. Figure 12 lists a comparison of top-30 showing 20-fold lead of Bitcoin over Litecoin.
Figure12. How the Current Crop of Virtual Currencies Stack Up

Such virtual currencies are also known as alt-coins for alternative crypto-currencies. alt-coins based upon SHA-256, the hashing algorithm for Bitcoin, include NMC: Namecoin, PPC: PPCoin (Peercoin), DVC: Devcoin, TRC: Terracoin, BTE: Bytecoin, IXC: Ixcoin, I0C: I0coin, FRC: Freicoin, and BLC: Blakecoin. In contrast, alt-coins such as Litecoin using scrypt, a password-based key derivation function that cannot be mined using ASICs, include besides LTC: Litecoin, NVC: Novacoin, FTC: FeatherCoin, MNC: MinCoin, BBQ: BBQcoin, TAG: Tagcoin, MEG: Memorycoin, and BTCs/BTC2: Bitcoin Scrypt. Like Bitcoins, most of these virtual currencies are mined similarly by using cryptographic proof of work concepts. Given central role in making the crypto-currencies possible, ‘cryptographic proof of work’ is anticipated to have a longer shelf-life than any of the above currencies. The future of money, whatever form it may take – virtual or quantum, will quite likely be "entangled" with the future evolution of ‘cryptographic proof of work.’ Hence, the focus of this report has been on most central concept underlying the current trajectory of e-evolution of money and global payments.


This research report represents the first known attempt with specific technical focus on cryptographic ‘proof of work’ in the context of virtual crypto-currencies such as Bitcoin. The cryptography, encryption and cryptanalysis technical focus of the report is intentional and related to Bitcoin’s innovative capabilities, vulnerabilities and threats. Situated somewhere along the trajectory between real money and quantum money, virtual crypto-currencies based upon ‘cryptographic proof’ represent a natural stage in the evolution of global finance. The feasibility and large-scale global implementation of Bitcoin as a crypto-currency has earned it admiration as a remarkable conceptual and technical achievement and an elegant solution. Its cryptographic solution enables creation and regulation of issue of crypto-currency, preventing its counterfeiting and double-spending, and securing its global transmission at minimal transaction cost while using little time. Central to all those interesting innovations is the cryptographic ‘proof of work’ supplanting trust in a third-party that is the central focus of the current study.


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  5. Ittay Eyal and Emin Gun Sirer. Majority is not Enough: Bitcoin Mining is Vulnerable. Computer Science > Cryptography and Security, Cornell University Library. November 15, 2013.
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  9. Nicola Jones. Google and NASA Snap Up Quantum Computer D-Wave Two. Scientific American. May 17, 2013.
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  28. U.S. Senate Committee on Homeland Security & Governmental Affairs. Beyond Silk Road: Potential Risks, Threats, and Promises of Virtual Currencies. November 18, 2013.


  61. CPU: central processing unit, GPU: graphics processing unit, FPGA: field-programmable gate array, ASIC: application-specific integrated circuit

*Pentagon Joint Chiefs: C4I-Cyber™: Beyond AI-Quantum Supremacy: Command-Control Supremacy™.
*US Air Force: AIMLExchange™: Invited Interviews: Top USAF Chief Scientist Pentagon Role.
*GIBC Digital Welcomes Leading Machine Learning & AI Expert to Lead $Billion AI-ML Data Center.
*Block Chain-Cloud Computing Pioneer: AI-Crypto Expert On Asia-Australia CEO Global Road Shows.
*MIT Computer Science & AI Lab AI-ML Executive Guide: MIT-Princeton AI-Quantum Faculty-SME.
*Princeton University Quant Trading-FinTech Crypto Presentations: Sponsors: Goldman Sachs, Citadel.

*2021 R&D Leading Worldwide Digital Practices: AI-ML-DL-Cyber-Crypto-Quantum-Risk-Computing
*2021 Joint Chiefs Of Staff: Beyond ABMS JADC2 to Quantum Uncertainty and Time-Space Complexity
*2020 Joint Chiefs Of Staff: AI-Quantum Autonomy in Space: Quantum PhD-Engineers Expert Keynote
*2021 Silicon Valley-Wall Street-Pentagon Digital Pioneer: Digital Startups to Trillion Dollar Enterprises
*2020 Making Quantum Computing Real for JADC2 With Qiskit: Quantum Communication & Networking
*2020 Beyond Data Protection to Command and Control (C2) Sustainability: U.S. Data Protection Act
*2019 Innovation Community (UK): Dr. Yogesh Malhotra: Future of AI-ML - Data Science, BlockChain
*2019 Journal of Financial Transformation: Capital Markets-Risks: AI Augmentation-Risk Management.
*2019 New York State Cyber Security Conference: AI-ML-GANs-DeepFakes: Cyber Risk of Deep Fakes.
*2016 New York State Cyber Security Conference: Beyond Predictive to Anticipatory Risk Analytics.
*2018 CFA Society Keynote: JP Morgan-Goldman Sachs Cases: Model Risk Management AutoML.
*2018 AFCEA C4I Cyber Conference: AI-ML-Cybersecurity Risk & Uncertainty Management Controls.
*2018 MIT Sloan-Computer Sc. & AI Lab AI-ML Executive Guide including RPA & Cognitive Automation
*2018 Princeton FinTech & Quant Conference: Invited Research Presentation: AI-ML-DL MRM.
*2016 Princeton Quant Trading Presentation: Beyond Model Risk Management to Model Risk Arbitrage.
*2015 Princeton Quant Presentation: Future of Finance Beyond 'Flash Boys': Managing Uncertainty.
*2018 Journal of Operational Risk: Toward 'Cyber-Finance’ Cyber Risk Management Frameworks.
*2017 National Association of Insurance Commissioners, Cyber Risk Insurance beyond VaR Models.
*2017 IUP Journal of Computer Sciences, April, Quantitative Modeling of Trust Management Protocols.
*Stress Testing for Cyber Risks: Cyber Risk Insurance Models beyond VaR: Risk, Uncertainty, & Profit.
*Integrated Enterprise Risk Management, Model Risk Management & Cyber-Finance Risk Management.
*Bridging Networks, Systems, Controls Frameworks: Cybersecurity Curricula & Standards Development.
*Advancing Cognitive Analytics Using Quantum Computing for Next Generation Encryption.
*Invited Princeton Quant Trading Presentations: 'Rethinking Finance' for Global Networked DeFi.
*Cybersecurity & Cyber-Finance Risk Management: Strategies, Tactics, Operations, Intelligence.

*Risk Management Framework: Penetration Testing: Banking-Finance Network VoIP Protocols.
*CyberFinance: Cybersecurity Risk Analytics Must Evolve to Survive Emerging Cyber Financial Threats.
*Beyond 'Bayesian vs. VaR' Dilemma: Managing Risk After Risk Management Failed for Hedge Funds.
*Measuring & Managing Financial Risks with Improved Alternatives Beyond Value-at-Risk (VaR).

*Markov Chain Monte Carlo Models for High-Dimensionality Complex Network Security Problems.
*Risk, Uncertainty, Profit: 'Knight Reconsidered': Model Risk Management in Cyber Risk Insurance.
*Cyber-Finance Risk Management: Strategies, Tactics, Operations, Intelligence: ERM to MRM.
*Number Field Sieve Cryptanalytic Algorithms for Efficient Prime Factorization on Composites.
*Bitcoin & Statistical Probabilistic Quant Methods: Financial Regulation: Hong Kong CPAs.
*Bitcoin Protocol & Block Chain: Model of 'Cryptographic Proof' Crypto-Currency Payment Systems.
*2015-2023 120+ SSRN Top-10 Rankings: AI-ML-Quant-Cyber-Crypto-Quantum-Risk Computing.
*2008 AACSB International Impact of Research Report: Among Finance Nobel Laureates Black-Scholes

Top Wall Street Investment Banks Quantitative Finance Projects & FinTech Ventures

US Air Force HQ AI-Machine Learning Commercial Exchange: Pioneering AGI To Save the World
AFRL Commercialization Academy: Building the Future of AGI: Griffiss Cyberspace & Drone™.
MIT Computer Science & AI Lab AI-Machine Learning Executive Guide: AI, ML, DL, NLP, RPA.
Princeton: Future of Finance: 'Rethinking Finance' for Era of Global Networked Digital Finance.

Journal of Financial Transformation:Capital Markets: AI Augmentation Cyber Risk Management.
New York State Cyber Security Conference: AI-ML-GANs-DeepFakes: Cyber Risk of Deep Fakes.
CFA Society Keynote: JP Morgan-Goldman Sachs Practices: Model Risk Management with AutoML.
AFCEA C4I Cyber Conference: AI-ML-Cybersecurity Risk & Uncertainty Management Controls.
MIT Sloan-Computer Sc. & AI Lab AI-ML Executive Guide including RPA & Cognitive Automation
Princeton FinTech Quant Conference: Research Presentation: AI-ML-Deep Learning MRM.
Journal of Operational Risk: 'Cyber-Finance’ Cyber Risk Management Frameworks of Practice.
National Association of Insurance Commissioners: Expert Paper: Cyber Risk Insurance Modeling
Princeton Quant Trading Presentation: Beyond Model Risk Management to Model Risk Arbitrage.
Princeton Quant Trading Presentation: Future of Finance Beyond 'Flash Boys': Uncertainty.
Quantitative Finance Risk Analytics Modeling Wall Street Investment Banks & VC Projects
Model Risk Management: Risk Management Analytics from 'Prediction' to 'Anticipation of Risk'
Quantitative Finance Risk Analytics, Econometric Analytics, Numerical Programming Models
Quantitative Finance Model Risk Management for Systemic-Tail Risks in Cyber Risk Insurance
JP Morgan Portfolio Optimization, VaR & Stress Testing: 17-Asset Class Portfolio
JP Morgan Portfolio Liquidity Risk Modeling Framework for $500-600Bn Portfolio
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Goldman Sachs Alumnus Asset Manager Large-Scale Data High Freq Econometric Models
Quantitative Finance, Risk Modeling, Econometric Modeling, Numerical Programming
Technologies of Computational Quantitative Finance & Risk Analytics and Risk Management
Algorithms & Computational Finance: C++, SAS, Java, Machine Learning, Signal Processing
Cybersecurity, Financial Protocols & Networks Protocols Analysis, and, Penetration Testing
Impact: Quantitative Finance, Quantitative Risk Analytics & Risk Management Projects
Digital Social Enterprise Ventures Creating Trillion $ Practices for Hundreds of Millions

Named among FinTech Finance & IT Nobel laureates for Real World Impact of Research
FinTech Innovations: Model Risk Arbitrage, Open Systems Finance, Cyber Finance, Cyber Insurance
AACSB International Reports Impact of Research among Black-Scholes, Markowitz, Sharpe
Research Impact Recognized among Finance & Information Technology Nobel laureates
120+ SSRN Top-10 Rankings: AI-Machine Learning; Cybersecurity; Computer Science, Quant Trading
FinTech Innovations: Model Risk Arbitrage, Cyber Finance, Cyber Risk Insurance Modeling
Computational Quantitative Finance Modeling & Risk Management Research Publications
Model Risk Management of Cyber Risk Insurance Models & Quantitative Finance Analytics
Thesis on Ongoing Convergence of Financial Risk Management & Cyber Risk Management
U.S. Federal Reserve & Office of the Comptroller of the Currency Model Risk Guidance
Bayesian VaR Beyond Value-At-Risk (VaR) Model Risks Exposed by Global Financial Crisis
Markov Chain Monte Carlo Models & Algorithms to Enable Bayesian Inference Modeling
OCC Notes Cybersecurity Risk & Cyber Attacks as Key Contributor to Banks' Financial Risk
Future of Bitcoin & Statistical Probabilistic Quantitative Methods: Global Financial Regulation
Models Validation Expert Panels: IT, Operations Research, Economics, Computer Science

Global, National, & Enterprise CxO Level FinTech-Cyber-Risk Analytics Ventures
CxO Think Tank that pioneered 'Digital' Management of Risk, Uncertainty, & Complexity
CxO Consulting: Global, National & Corporate Risk Management Practices Leadership
CxO Guidance: Cyber Defense & Finance-IT-Risk Management: Uncertainty & Risk
CxO Keynotes: Conference Board, Silicon Valley, UN, World Economy: Uncertainty & Risk
The Future of Finance Project Leading Quantitative Finance Practices at Elite Conferences
The Griffiss Cyberspace Cybersecurity Venture Spans Wall Street and Hi-Tech Research
UN Quantitative Economics Expert Paper & Keynote on Global Economists Expert Panel
National Science Foundation Cybersecurity & Cybercomputing National Expert Panels
Digital Social Enterprise Innovation Ventures Pioneering the Future of Risk and Quant
Global Footprint of Worldwide World-Leading CxO Risk Management Ventures & Practices

Digital Transformation - Artificial Intelligence: ML-DL-NLP-RPA - Cyber-Crypto Computing - Post AI-Quantum Computing

30-Years as World-Leading AI-Cyber-Global Digital Transformation Networks Pioneer: Post-WWW to Post AI-Quantum Computing

"There are many definitions of knowledge management. It has been described as "a systematic process for capturing and communicating knowledge people can use." Others have said it is "understanding what your knowledge assets are and how to profit from them." Or the flip side of that: "to obsolete what you know before others obsolete it." (Malhotra) "
- U.S. Department of Defense, Office of the Under Secretary of Defense (Comptroller)

"KM is obsoleting what you know before others obsolete it and profit by creating the challenges and opportunities others haven't even thought about -- Dr. Yogesh Malhotra, Inc. Technology"
- U.S. Defense Information Systems Agency Interoperability Directorate

"If you spend some time at [the digital research lab] founded by Dr. Malhotra you will be blessed by some of the world's most astute thinking on the nature of knowledge and its value."
- U.S. Army Knowledge Symposium, Theme: "Knowledge Dominance: Transforming the Army...from Tooth to Tail", Department of Defense, United States Army.

"We are observing diminishing credibility of information technologists. A key reason for this is an urgent need to understand how technologies, people and processes together combine to influence enterprise performance. Today's effective CIO doesn't deliver IT. He delivers business transformation services."
- Yogesh Malhotra, Journal of Knowledge Management, 2005
- United States Air Force Research Lab CIO Col. Tom Hamilton
in presentation to the Armed Forces Communications Electronics Association titled 'Enterprise IT Solutions Are Tough But They're Tougher If You're Stupid', July 21, 2005.

"Knowledge Management refers to the critical issues of organizational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." -- Yogesh Malhotra
- United States Department of Navy

"Dr. Yogesh Malhotra, PhD, drawing upon numerous sources, proposes several theories as to how IT can be used to drive the change of organizations. As environments become more turbulent, organizations must adapt at the same rate to maintain its advantage. Among his theories are that the turbulent environments (in this case, business, but can translate to the turbulent military conflict environment) drive organizations to use IT for empowering workers at all levels, increasing span of control, and increasing lateral communications."
- United States Marine Corps, Reorganization Of The Marine Air Command And Control System To Meet 21St Century Doctrine And Technology, Thesis, September 2001.

"The self-organizing capacity of dynamically adaptive systems is amazing. They tend to eliminate redundancy, minimize connections, and establish priorities--all without outside direction. When something is organized, we tend to believe that someone organized it, some outside influence. But that's not necessarily so. Self-organization is a process in which the organization of a system occurs spontaneously based on the action of its members, without this process being controlled by an external system. The richness of possible behavior increases rapidly with the number of interconnections and the level of feedback. (Malhotra) "
- U.S. Army War College Quarterly

"Dr. Malhotra argues in Business Process Redesign that reengineering is the notion of discontinuous thinking -- recognizing and breaking away from outdated rules and fundamental assumptions. He suggests that reengineering principles are organized around outcomes, and that people who use the output should perform the process. This links parallel activities instead of integrating results, and puts the decision point where the work is performed (Malhotra, 1996). Integrating the DPW processes further into the installation staff can achieve these outcomes. Seventy percent of Business Process Redesigns (BPR) fail because of business focus on cost-cutting and narrow technical approaches (Malhotra, 1996). The installation commanders should decide how DPWs could best serve the community. They should have the opportunity to focus on efficient output and not on restructuring to cut cost. Developing the Corps as the primary service provider narrows the commander's options and does not solve the problem, merely the symptoms. The ultimate success of BPR depends on the experience of people who execute it and how well they apply their creativity to redesigning the processes."
- U.S. Army Management Staff College

"These activities are often described as "knowledge management." See Knowledge Management, in the World Wide Web Virtual Library, edited by Yogesh Malhotra. (Accessed June 16, 1998)....The terms "marshalling" and "mobilization" are intended here to represent two major activities of knowledge management in U.S. national security decisionmaking. Although others may describe and classify basic knowledge-building activities differently, "knowledge management" has been accepted as an umbrella term. See. for example, TheWorld Wide Web Virtual Library on Knowledge Management, edited by Yogesh Malhotra, (Accessed June 16, 1998)..."
- U.S. Air Force Colonel Roc A. Myers, Colonel (s), Harvard University Air Force National Defense Fellow with the Program in 1997-98. Strategic Knowledgecraft: Operational Art for the Twenty-First Century, Roc A. Myers, Prepared while an Air Force National Defense Fellow with the Program in 1997-98 (September 2000).

"Seventy percent of BPR projects fail. Three primary obstacles inhibit the success of reengineering projects: Lack of sustained management commitment and leadership -- It is critical that senior leadership not only support BPR but also be a vocal advocate. Unrealistic scope and expectations -- It is important to manage expectations. BPR is not a panacea that will cure all ills. Resistance to change -- The world is changing all the time and the pace of change continues to accelerate. It will continue to change whether we participate or not. We must change with it or be left behind. AIT provides AIS program managers the opportunity to completely reexamine and reengineer their entire business process, because it offers capabilities not previously available in terms of timeliness and accuracy of data capture. During the operational prototype, the Air Force provided an excellent example of a reengineered business process as a result of AIT. The Supply Asset Tracking System (SATS) is a front-end server that integrates AIT with the supply AIS, the Standard Base Supply System (SBSS). SATS uses linear bar codes for tracking and inventory purposes and smart cards for personal identification to verify receipt and establish personal accountability of property. (Malhotra) "
- U.S. Department of Defense Logistics Implementation Plan

"Knowledge Management caters to the critical issues of organisational adaption, survival and competence in the face of increasingly discontinuous environmental change ... Essentially, it embodies organisational process that seek synergistic combination of data and information processing capacity of information technologies and the creative and innovative capacity of human beings." - Yogesh Malhotra
- Royal Australian Air Force (RAAF) AIRCDRE John Blackburn, Director General Policy and Planning - Air Force (DGPP-AF), Royal Australian Air Force (RAAF), in Air Power Conference 2000.

"First intangible assets are defined in relation to core competencies of the firm. Each core competence is a combination of intangible assets such as knowledge and skills, standards and values, explicit know-how and technology, management processes and assets, and endowments such as image, relationships, and networks. Knowledge creation is the core competence of any firm (Malhotra, 2000)."
- Government of UK, Ministry of Defence

"Malhotra noted the importance of Information Systems for organizational learning, mentioning a series of techniques, methods and tools that can foster organizational learning at many steps of the process: knowledge acquisition, creation and distribution [Malhotra, 1996]."
- Canadian Department of National Defence, Canada, Defence R&D Canada

"Knowledge Management caters to the critical issues of organisational adaption, survival and competence in the face of increasingly discontinuous environmental change. Essentially, it embodies organisational process that seek synergistic combination of data and information processing capacity of information technologies and the creative and innovative capacity of human beings. -- Yogesh Malhotra"
- Air Force, Australia, Director General Policy and Planning

"According to Malhotra, KM ensures that right knowledge is applied at the right place and time and it is about doing the right thing instead of doing things right. Its application to R&D will avoid unnecessary duplication of research. It can help support both individual and organizational learning from past successes and failures while guiding future actions and changes."
- International Atomic Energy Agency

"The Knowledge Management (KM) area has become so diverse over the past ten years as researchers have begun to investigate not only the mechanics of knowledge creation and transfer but also of social and cultural issues that are of importance in understanding this topic. KM is the process of leveraging and utilizing the vast, untapped potential of both implied and documented knowledge to achieve optimal performance, both are equally important for improving performance. Knowledge Management enables businesses to exchange and optimize the knowledge and experience. "Knowledge Management caters for the critical issues of organisational adoption, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings" (Dr. Yogesh Malhotra 1997)."

"In his latest book, Knowledge Management and Virtual Organisations, KM luminary, Dr. Yogesh Malhotra, offers some cautionary advice. He exposes three myths often associated with KM solutions. The first of these is that knowledge management technologies can deliver the right information to the right person at the right time. This assumes businesses will develop incrementally in stable markets. However as Malhotra says, "the new business model in the Information Age is marked by fundamental, not incremental change. Businesses can't plan long-term; instead, they must shift to a more flexible 'anticipation of surprise' model. Thus it is impossible to build a system that predicts who the right person at the right time even is, let alone what constitutes the right information."
- Microsoft Corporation

"All can be used to further the goal of keeping the channels of communication open to allow for the exchange of issues and ideas within an organization. According to BRINT Institute chairman and CKO Dr. Yogesh Malhotra, "The key issue is not about the latest information technologies, but whether those technologies are used within, and for facilitating, a culture of information sharing, relationship building and trust." With communication and trust, set within the solid framework of a component architecture, your business can harness that elusive ability to get the right information to the right people at the right time for the right business purposes."
- Cisco Systems, Inc.

"According to Yogesh Malhotra, Knowledge Management practitioner and web author, "Knowledge Management is a brand new field emerging at the confluence of organization theory, management strategy, and management information systems." Breaking apart this definition, Knowledge Management can be defined as an internal, corporate strategy. Knowledge Management can also stand alone as a separate, Information Technology program. Malhotra is right on target when he states that Knowledge Management is a brand new field. Knowledge Management began receiving airplay in 1996. At that time, Tom Davenport wrote in CIO Magazine that a chief knowledge officer "captures and leverages structured knowledge, with information technology as a key enabler." Expanding upon Malhotra and Davenport's definitions, Knowledge Management within NCR Corporation can be defined via a business objective (strategic), a method of Knowledge Management delivery (the management information system), and a role within the organization. NCR's objective is to create, capture, and disseminate knowledge."
- NCR Corporation

"Institutionalization of 'best practices' by embedding them in information technology might facilitate efficient handling of routine, 'linear,' and predictable situations during stable or incrementally changing environments. However, when this change is discontinuous, there is a persistent need for continuous renewal of the basic premises underlying the 'best practices' stored in organizational knowledge bases. -- Yogesh Malhotra in Knowledge Management in Inquiring Organizations"
- Vice President, SAP, North America in SAP Portals ASUG Meeting

"Often used synonymously, the terms knowledge and information, are actually different. Information facilitates knowledge, and can exist without knowledge. Knowledge, however, cannot exist without information. To simplify the concept, Dr. Yogesh Malhotra, renowned scholar on Knowledge Management, defines "Knowledge" as potential for action that has an immediate link to performance. This definition suggests that a person's response or action, or contextual consideration for future action, based on information, is knowledge."
- VeriSign Inc.

"It is generally agreed that the greatest challenges to knowledge management initiatives are resistance to change in both an organization's information-sharing culture and the business processes that occur as a result. K.M. Malhotra defined the problem as follows: Culture is the most difficult component of KM to define, quantify, measure and influence. However, the success or failure of an effective KM program is almost solely dependant upon whether an organization's culture encourages or hinders sharing and transferring knowledge freely within the organization's structure. One thing is certain: an organization's cultural predisposition toward the free transfer of knowledge is largely reflective of the proactive stance demonstrated by the organization's leadership."
- Northrop Grumman

"Il Knowledge Management essenzialmente coinvolge processi organizzativi che cercano di realizzare una combinazione tra le capacità di elaborazione di dati e informazioni e le capacità creative e innovative degli esseri umani. (fonte: Yogesh Malhotra, Ph.D., Knowledge Management for the New World of Business...)"
- Microsoft, Italy

"Knowledge Management refers to the critical issues of organisational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organisational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings. This definition proposed by Dr. Yogesh Malhotra summarises a key issue for e-learning strategies and the way they will impact professional training and companies' organisation policies."
- European Commission

"In the Committee's view, definitions that treat the area as a discipline rather than a mere collection of technologies best encapsulate what knowledge management means. For example, Malhotra says:, "Knowledge Management caters to the critical issue of organisational adaptation, survival and competence in the face of increasingly discontinuous environmental change..."
- Parliament of Victoria, Australia

"It is therefore impossible to typify the roles of Knowledge Management workers other than the CKO, and indeed these roles themselves are in a constant state of change. Dr. Yogesh Malhotra defines this as follows: Given the need for autonomy in learning and decision making, such knowledge workers would also need to be comfortable with self-control and self-learning."
- Government of UK

"We are facing "permanent white-waters" which demands strategies for adaptation to uncertainty in contrast to the conventional emphasis on optimisation based on prediction (Malhotra 1999). To quote a decision-maker in a large multinational firm; "The future is moving so quickly that you can't anticipate it. We have put a tremendous emphasis on quick response instead of planning. We will continue to be surprised, but we won't be surprised that we are surprised. We will anticipate the surprise." (Malhotra 1999)."
- Government of Sweden

"It is difficult, not to say impossible, to replace the significance of individual or collective face-to-face interactions in the sharing of tacit knowledge and articulating it as explicit in an organization, even if rapid development of interactive multimedia applications combining text, image and sound offers increasingly advanced communication potential. Virtual forms of working and work organization might at best supplement, but never totally replace, self-managing teams with close physical and social contacts, for instance, as a forum for learning. (Malhotra) "
- Government of Finland

"A key feature of knowledge management is the sharing of knowledge as opposed to simply the dissemination of information. Knowledge has a different quality to information. Knowledge includes human experience and the ability to make complex judgments based on past experience. Information is more about mere data whereas knowledge is 'potential for action'. (Malhotra)
- Government of Australia

"Ich glaube die Technology ist der leichtere Teil des Ganzen. Die wirkliche Herausforderung stecken doch darin wie die Geschäfts-Prozessen und die darauf aufbauenden Geschäfts- Modelle in Einklang gehalten werden mit den radikalen änderungen in der Geschäftswelt und dem Berufsbild der "Knowledge Worker."[Malhotra, 1993]."
- Government of Austria

"Knowledge management refers to the critical issues of organizational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings," says Dr. Yogesh Malhotra, founding chairman and chief knowledge architect of the BRINT Institute, in an interview with Alistair Craven. Widely recognized as a knowledge management pioneer, Malhotra adds, "Knowledge management is more about the pragmatic and thoughtful application of any concept or definition, as it is not in the definition but in real world execution where opportunities and challenges lie. Any definition therefore must be understood within the specific context of expected performance outcomes and value propositions that answer the question 'Why' about relevance of KM.""
- U.S. Embassy, American Center, New Delhi, India

"Knowledge management, which is a new field emerging from the confluence of organisation theory, management strategy and management information systems, is viewed as an essential driver for innovation. According to Malhotra "Knowledge Management caters to the critical issues of organisational adaption, survival and competence in face of increasingly discontinuous change. Essentially it embodies organisational processes that seek a synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings"."
- Government of South Africa

"Estes ativos do conhecimento aumentam com o uso e daí a importância de as empresas identificarem o que sabem e manterem todo o esforço para desenvolverem área de gestão do conhecimento. A gestão do conhecimento, segundo Malhotra é a capacidade de catalizar os aspectos críticos de adaptação, sobrevivência e competência, buscando uma combinação sinérgica da capacidade de processar informações e conhecimento com a capacidade criativa e inovativa dos seres humanos. (MALHOTRA, 1999)."
- Government of Brazil

"Esta enumeración no implica que algún factor no pueda ocupar a la vez distintas posiciones. La principal característica del nuevo entorno de las organizaciones es su alto nivel de incertidumbre. Por incertidumbre entendemos "la diferencia entre la cantidad de información requerida para realizar una tarea y la cantidad de información ya en poder de la organización" YOGESH, Malhotra.""
- Government of Argentina

"The disconnect between IT expenditures and the firms' organizational performance could be attributed to an economic transition from an era of competitive advantage based on information to one based on knowledge creation." - Yogesh Malhotra
- Government of Mauritius

"The focus of knowledge management is on 'doing the right thing' instead of doing things right’, (Yogesh Malhotra, 2001). The emphasize is that that knowledge management provides framework within which the organization views all processes of the activities to sustain the business and/or ensuring the business survival. Within the army organization, there is no difference. The army needs to keep pace with the technology advancement preparing for the increasingly dynamic and unpredictable regional and world environment."
- Royal Military Police Directorate, Army HQ, Malaysia

"Knowledge Management embodies organnizational processes that seek synergistic combinations of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." -- Yogesh Malhotra, Ph.D."
- Government of Malta

"Dr. Yogesh Malhotra, one of the experts and founder contributor in the development of concept of KM has defined the KM as under : "Knowledge Management caters to the critical issues of organizational adaptation, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings". As it is clear from this definition that objective of Knowledge Management as a crucial management function is not only to survive under changing environment but also to make the organisation adaptable and competitive. The same is particularly applicable for Banks in India, since they are now operating under such a dynamic business environment."
- Indian Banks' Association, India

"Dr. Yogesh Malhotra, the Founder and Chief Knowledge Architect of BRINT, and a well-known expert in the field of K-economy, opines: "The challenges facing us as we enter the 21st Century are formidable. Globalization, Information Technology and Shareholders' Values are transforming the world. To meet these challenges is to become a knowledge-creating or knowledge intensive organization"."
- Indian Banks' Association, India

"Knowledge Management has structural and functional basis in the IM (Information Management or IRM. The main difference is the high degree of dynamic activity involved in the KM system. To summarize in the words of Dr. Malhotra, (10) 'use of the information and control systems and compliance with pre-defined goals, objectives and best practices may not necessarily achieve long-term organizational competence. This is the world of 're-use,' 're-engineering', 're-cycling' etc, which challenges the assumptions underlying the 'accepted way of doing things.' This world needs the capability to understand the problems afresh given the changing environmental conditions. Knowledge management focuses on 'doing the right thing' instead of 'doing things right.'"
- Indian Statistical Institute, Bangalore, India

"Knowledge Management caters to the critical issues of organizational adaption, survival and competence in face of increasingly discontinuous environmental change. Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings."
- National Academy of Psychology (NAOP), India

"Finally, all who are concerned with IT security issues should understand -- and appreciate -- the difference between information and knowledge. Information, writes Yogesh Malhotra, PhD, is embedded in a computer -- while knowledge is embedded in people. "Information generated by a computer is not a very rich carrier of human interpretation for potential action," he writes. "Computer are merely tools, however great their information-processing capabilities may be."
- Chairman of the Board, The Institute of Internal Auditors

"Leadership Quote of the Week: The focus of knowledge management is on doing the right thing instead of doing things right... Yogesh Malhotra"
- Chartered Management Institute, UK

"Dr. Yogesh Malhotra, founder of the Brint Institute and a pioneer in knowledge management, posits that "the basic premise is that you can predict how and what you'll need to do and that IS can simplify this and do it efficiently". However, the new business model, he says, is marked by fundamental, not incremental, change and businesses can't plan long-term. Instead, they must shift to a more flexible "anticipation of surprise" model, making it impossible to build a system that can predict what is the right information to be delivered to the right person at the right time. This is not to say that information technology has been displaced from the knowledge management equation; its place has been preserved by a growing realisation among developers that software alone cannot automatically be seen as the solution."
- National President of the Australian Computer Society, Australia

"Yogesh Malhotra, founding chairman and chief knowledge officer for the BRINT Institute in Syracuse, New York, believes that the fundamental distinction between data and knowledge plays a major role in whether a system is designed for adaptation and quick response to change. "Dynamic and radically changing environments overwhelm the deterministic logic of a structured model, resulting in a 70 percent failure rate that has characterized implementations of knowledge management models" says Malhotra. Recounting his visit to a Silicon Valley hi-tech consulting firm, Malhotra attributes most failed corporate intranet initiatives to the above fallacy... Malhotra says that once routinized for efficiency and optimization, knowledge-harvesting processes may be delegated to others. However, supply managers need to be more proactively involved in knowledge-creation and knowledge-renewal processes..."
- Institute for Supply Management (ISM)

"Yogesh Malhotra, founding Chairman and Chief Knowledge Architect of the BRINT Institute states: "Knowledge management software is not a canned solution; "Knowledge management technologies cannot always deliver the right information to the right person at the right time; "Information technologies cannot store human intelligence and experience; "Knowledge management systems do not account for renewal of existing knowledge and creation of new knowledge; "Greater incentives are needed for workers to contribute quality content to KMS." Improper use of KMS databases can waste resources if an organization does not really know what knowledge assets it possesses and fails to capitalize on potential new initiatives."
- National Association of Realtors

"Similarly, Dr. Yogesh Malhotra, the famous "Knowledge Architect", wrote a cautionary article on "When Best [Practices] Becomes Worst", Momentum: the Quality Magazine of Australasia, Quality Society of Australasia, NSW (Australia, 2002). In fact, the conditions for producing and utilizing knowledge workers are not a question of the persons concerned merely acquiring subject-matter expertise, problem-solving competency and communication skills. It is essential to provide an environment where such persons can operate and flourish. In the same vein, one of Malhotra's recent books (monograph) for UNESCO discusses knowledge work taking place in "hyper turbulent organizational environments.""
- International Labour Office (ILO)

"Knowledge Management - Discipline that seeks to improve the performance of individual organizations by maintaining and leveraging present and future value of knowledge assets, encompassing both human and automated activities. " Knowledge Management caters to the critical issues of organizational adaption, survival and competence in face of increasingly discontinuous environmental change.... Essentially, it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings." - Dr. Yogesh Malhotra"
- U.S. Department of Health & Human Services

"The mechanistic model of information processing and control based upon compliance is not only limited to the computational machinery, but extends to specification of goals, tasks, best practices and institutionalized procedures to achieve the pre-specified outcomes." -- Yogesh Malhotra
- European Health Management Association, Ireland

"KM has become an increasingly important management discipline in recent years. Nevertheless, some say the phrase KM is unhelpful because 'knowledge is not a "thing" that can be "managed"1. They challenge the 'dominance and control model' that often underlies traditional views of knowledge and organisational management and development. They assert instead the notion that knowledge is largely cognitive, tacit and highly personal. They champion the fundamental role of people and the social interactive basis of knowledge sharing and creation. (Malhotra, Y..) "
- UK Department of Health

"Knowledge management is viewed as an essentialdriver for innovation. According to Malhotra, "Knowledge Management caters to the critical issuesof organisational adaptation, survival and competencein the face of increasingly discontinuous change.Essentially it embodies organisational processes thatseek a synergistic combination of the data andinformation processing capacity of informationtechnologies, and the creative and innovative capacityof human beings"."
- United Nations Development Program (UNDP), Geneva, Switzerland

"Adaptive Learning (See: Double Loop Learning): "Adaptive learning, or, single-loop learning, focuses on solving problems in the present without examining the appropriateness of current learning behaviors." -- Malhotra, Y., Organizational learning and learning organizations: an overview."
- World Health Organization (WHO)

"Dr. Yogesh Malhotra is regarded among the world's most influential practitioners and thought leaders on knowledge management. Widely recognized as a knowledge management pioneer, in this extensive interview read what Dr. Malhotra has to say about knowledge, information, technology and chasing success in this field."
- Emerald Group Publishing Ltd (UK)

"Dr. Yogesh Malhotra in the US is a leader in the knowledge management field. In a recent article written for the US Journal for Quality & Participation, he has pointed to a problem in relation to organisations investing heavily in information technology but not realising gains in terms of knowledge creation."
- Irish Times, Ireland

"Be that as it may, there is no doubt that domestic enterprises, faced by a complete bankruptcy of knowledge and ideas, will, some day, understand the value of the knowledge held by their employees. In the meantime, they would do well to study the writings of Dr. Yogesh Malhotra, an authority on technology and innovation management, business performance, and corporate strategy issues related to information systems, knowledge management, e-business and electronic commerce, business decision models, and new organisation forms."
- The Hindu, A Major National Daily Newspaper, India

"Professor Yogesh Malhotra of Syracuse University, New York, and expert in this field, has recently argued that one of the reasons for this failure is that more often than not knowledge management is practiced in isolation and does not take into account the dynamism of the external environment."
- Malaysian Business, Malaysia

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