Blockchain 51% Attacks – Lessons Learned For Developers And Trading Platform Operators

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Blockchain 51% Attacks – Lessons Learned For Developers And Trading Platform Operators

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Once purely theoretical, “majority” or “51%”
attacks on public blockchains have dealt participants a reality
check: The fundamental assumption of Satoshi Nakamoto’s 2008 Bitcoin
(that computing power will remain sufficiently
decentralized in blockchain networks that rely on a “proof-of-work
consensus mechanism) can in practice actually be exploited
to enable double spending.

“The system is secure as long as honest nodes
collectively control more CPU power than any cooperating group of
attacker nodes…. If a majority of CPU power is controlled by
honest nodes, the honest chain will grow the fastest and outpace
any competing chains. To modify a past block, an attacker would
have to redo the proof-of-work of the block and all blocks after it
and then catch up with and surpass the work of the honest
– Satoshi Nakamoto, Bitcoin: A Peer-to-Peer
Electronic Cash System

These incidents have provided opportunities for developers of
both public and private blockchains, as well as operators of
blockchain-based digital asset trading platforms, to learn from the
first generation of blockchain deployments.

Recently, two reorganizations of the Bitcoin Gold (BTG)
blockchain (the hard fork of Bitcoin) resulted in 7,167 BTG (then
approximately $87,500) being double spent. It has been suspected
that the computing power necessary to maintain this grift was
rented through NiceHash, a hash power marketplace.

While not nearly as large a haul as the over 388,000 BTG (then
approximately $18 million) heist in May 2018 or the attack executed on
the Ethereum Classic (ETC) blockchain in January 2019 in which 219,500 ETC (then
approximately $1.1 million) was double spent, this latest 51%
attack on a major public blockchain serves as a reminder of the
practical implications of this known vulnerability.

What is a 51% Attack?

The Bitcoin Gold and Ethereum Classic blockchains, among other
high-profile blockchains, determine “truth” using a proof-of-work consensus algorithm, whereby
network participants compete for the right to add blocks to the
blockchain by expending computing power to solve complex
computational problems the fastest. Nodes on such a blockchain
network always consider the longest version of the blockchain
(i.e., the blockchain that took the most computing work to
generate) to be the correct one.

A 51% attack is when a malicious actor controls a sufficient
percentage of the network’s computing power such that it is
able to build and verify blocks quicker than the rest of the
network can, resulting in the network accepting the attacker’s
version of the blockchain as the “truth.” By doing so, an
attacker can decide which submitted transactions are approved and
added to the blockchain. It can also erase old transactions if it
is able to build a new “longest chain” starting from a
block that came before those transactions were added to the
blockchain, as that new longest chain would not include those

An attacker could, for example, use this influence to spend its
cryptocurrency (e.g., exchange it for another cryptocurrency or USD
on a trading platform) and then go back and erase that transaction,
giving the attacker possession of the “spent”
cryptocurrency again. This would enable the attacker to spend that
same cryptocurrency twice – a “double spend.”

There are limits to what a 51% attacker can do, however. The
farther back in the blockchain a transaction is, the more
exponentially difficult it is to erase it. This is due to the
immense computational work required to build an alternate
“longest chain” (which would need to stem from a block
before the transaction to be erased) faster than the rest of the
blockchain network can continue building the incumbent chain. Also,
while a 51% attacker can potentially erase old transactions, it
cannot fabricate new transactions using other blockchain network
participants’ addresses, as it is not possible to do so without
having the private keys associated with those addresses (which are
necessary to digitally “sign” transactions). In the words
of Satoshi Nakamoto’s whitepaper, attackers cannot
“[create] value out of thin air or [take] money that never
belonged to the attacker.”

Although the largest blockchain networks, such as Bitcoin (BTC)
and Ethereum (ETH), have a sufficiently high hash rate to make it
unlikely for a would-be 51% attacker to amass the computing power
necessary to take control, a number of developments since the
Bitcoin blockchain launched in 2009 have increased the likelihood
of blockchains with lower hash rates being compromised. In fact, websites exist
that calculate the theoretical cost of a 51% attack on the largest
blockchain networks, and those costs are relatively low outside of
the top few blockchains. Application-specific integrated circuits
(ASICs) purpose-built to mine cryptocurrencies and powerful
graphics processing units (GPUs) have flooded the mining community, mining pools have consolidated resources and hash
power marketplaces have made significant computing power available
to rent. Looking ahead,
quantum computing
also could pose a threat if concentrated in
the hands of malicious actors.

Lessons Learned

As with many technological innovations, running blockchain
deployments through the gauntlet of real-world use has provided
valuable insights that can inform the next generation of
developments. As developers and digital asset trading platform
operators continue to iterate, they may want to consider the
following points:

  • Engineer 51% Attack
    Proof-of-work consensus algorithms could
    potentially be strengthened with a mechanism that detects
    indicators of 51% attacks and, by design, hinders them. For
    example, Horizen (formerly ZenCash) has suggested in a whitepaper instituting a block acceptance time
    delay for any alternate “longest chain” that a 51%
    attacker keeps hidden until it is ready to broadcast to the
    network, which would penalize the attacker proportionately based on
    the number of blocks it secretly builds in constructing its
    “dishonest chain”. This would give the correct
    “honest chain” an additional window of time to catch up
    to and overtake the dishonest chain, making it more difficult for a
    51% attack to be successful.

  • Alternate Consensus
    Although each type of consensus mechanism has
    its own drawbacks, consider variations of “proof-of-work”
    or other consensus algorithms, such as “proof-of-stake” (in which the probability
    of a particular node being selected to create a new block is based
    on the percentage of the blockchain’s total tokens owned by
    that node).

  • Even Out the Hash Rate
    Playing Field:
    Consider guarding against concentrations of
    computing power by instituting measures to maximize the
    decentralization of hash rate, such as by designing the blockchain
    to be resistant to the advantages of ASICs, GPUs or quantum

  • Resisting Quantum
    It is important to consider the implications of

    quantum computing
    on systems that rely on cryptography for
    security and on blockchains that utilize proof-of-work consensus
    mechanisms, particularly if quantum computers are purpose-built to
    perform proof-of-work calculations in a manner that exceeds the
    speed of current specialized ASIC hardware. During the period
    before quantum computing achieves widespread adoption, there may be
    heightened risks associated with using systems that are not
    quantum-resistant, as a few bad actors with access to quantum
    computers could potentially use them to overpower a blockchain
    network more easily than they could with current technology.

  • Private and Hybrid Blockchain
    In the context of private and hybrid
    blockchains, where the number of nodes on the network are likely
    significantly fewer than their public counterparts and there may be
    some degree of centralization, it is important that the governance
    mechanisms coded into the blockchain appropriately anticipate
    scenarios in which control over certain nodes may be compromised.
    From a legal perspective, it is also critical that the governing
    legal agreements that the participants enter into appropriately
    address how risk will be allocated and how issues will be

  • Longer Exchange Hold
    Trading platforms may benefit from requiring longer
    hold times before deposited tokens can be traded or withdrawn
    – waiting for more “new block” confirmations after
    a deposit is made can help reduce the risk of a 51% attack being
    sustained for long enough for the attacker to complete a double

  • Avoid Weak Links Ancillary to
    Despite the occurrences of 51% attacks, many
    of the incidents that have resulted in the theft, loss or
    inaccessibility of blockchain-based digital assets were due to
    flaws in technology ancillary to blockchains (for example, flaws in

    digital wallets
    or smart contracts that interact with, or are
    deployed on, blockchains), rather than the underlying blockchain
    itself. Care should be taken to thoroughly test those potential
    weak links before deployment or use. Developers of products that
    build on top of, or interface with, blockchains should be sure to
    draft their governing license terms or terms of service to
    appropriately insulate them from liability for defects or

Blockchain 51% Attacks – Lessons Learned For Developers And
Trading Platform Operators

The content of this article is intended to provide a general
guide to the subject matter. Specialist advice should be sought
about your specific circumstances.

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