The Miner's Dilemma

An open distributed system can be secured by requiring participants to present proof of work and rewarding them for participation. The Bitcoin digital currency introduced this mechanism, which is adopted by almost all contemporary digital currencies and related services. A natural process leads participants of such systems to form pools, where members aggregate their power and share the rewards. Experience with Bitcoin shows that the largest pools are often open, allowing anyone to join. It has long been known that a member can sabotage an open pool by seemingly joining it but never sharing its proofs of work. The pool shares its revenue with the attacker, and so each of its participants earns less. We define and analyze a game where pools use some of their participants to infiltrate other pools and perform such an attack. With any number of pools, no-pool-attacks is not a Nash equilibrium. With two pools, or any number of identical pools, there exists an equilibrium that constitutes a tragedy of the commons where the pools attack one another and all earn less than they would have if none had attacked. For two pools, the decision whether or not to attack is the miner's dilemma, an instance of the iterative prisoner's dilemma. The game is played daily by the active Bitcoin pools, which apparently choose not to attack. If this balance breaks, the revenue of open pools might diminish, making them unattractive to participants

On Cryptocurrency Wallet Design

The security of cryptocurrency and decentralized blockchain-maintained assets relies on their owners safeguarding secrets, typically cryptographic keys. This applies equally to individuals keeping daily-spending amounts and to large asset management companies. Loss of keys and attackers gaining control of keys resulted in numerous losses of funds. The security of individual keys was widely studied with practical solutions available, from mnemonic phrases to dedicated hardware. There are also techniques for securing funds by requiring combinations of multiple keys. However, to the best of our knowledge, a crucial question was never addressed: How is wallet security affected by the number of keys, their types, and how they are combined? This is the focus of this work. We present a model where each key has certain probabilities for being safe, lost, leaked, or stolen (available only to an attacker). The number of possible wallets for a given number of keys is the Dedekind number, prohibiting an exhaustive search with many keys. Nonetheless, we bound optimal-wallet failure probabilities with an evolutionary algorithm. We evaluate the security (complement of failure probability) of wallets based on the number and types of keys used. Our analysis covers a wide range of settings and reveals several surprises. The failure probability general trend drops exponentially with the number of keys, but has a strong dependency on its parity. In many cases, but not always, heterogeneous keys (not all with the same fault probabilities) allow for superior wallets than homogeneous keys. Nonetheless, in the case of 3 keys, the common practice of requiring any pair is optimal in many settings. Our formulation of the problem and initial results reveal several open questions, from user studies of key fault probabilities to finding optimal wallets with very large numbers of keys. But they also have an immediate practical outcome, informing cryptocurrency users on optimal wallet design

Majority is not Enough: Bitcoin Mining is Vulnerable

The Bitcoin cryptocurrency records its transactions in a public log called the blockchain. Its security rests critically on the distributed protocol that maintains the blockchain, run by participants called miners. Conventional wisdom asserts that the protocol is incentive-compatible and secure against colluding minority groups, i.e., it incentivizes miners to follow the protocol as prescribed. We show that the Bitcoin protocol is not incentive-compatible. We present an attack with which colluding miners obtain a revenue larger than their fair share. This attack can have significant consequences for Bitcoin: Rational miners will prefer to join the selfish miners, and the colluding group will increase in size until it becomes a majority. At this point, the Bitcoin system ceases to be a decentralized currency. Selfish mining is feasible for any group size of colluding miners. We propose a practical modification to the Bitcoin protocol that protects against selfish mining pools that command less than 1/4 of the resources. This threshold is lower than the wrongly assumed 1/2 bound, but better than the current reality where a group of any size can compromise the system

Cache Serializability: Reducing Inconsistency in Edge Transactions

Read-only caches are widely used in cloud infrastructures to reduce access latency and load on backend databases. Operators view coherent caches as impractical at genuinely large scale and many client-facing caches are updated in an asynchronous manner with best-effort pipelines. Existing solutions that support cache consistency are inapplicable to this scenario since they require a round trip to the database on every cache transaction. Existing incoherent cache technologies are oblivious to transactional data access, even if the backend database supports transactions. We propose T-Cache, a novel caching policy for read-only transactions in which inconsistency is tolerable (won't cause safety violations) but undesirable (has a cost). T-Cache improves cache consistency despite asynchronous and unreliable communication between the cache and the database. We define cache-serializability, a variant of serializability that is suitable for incoherent caches, and prove that with unbounded resources T-Cache implements this new specification. With limited resources, T-Cache allows the system manager to choose a trade-off between performance and consistency. Our evaluation shows that T-Cache detects many inconsistencies with only nominal overhead. We use synthetic workloads to demonstrate the efficacy of T-Cache when data accesses are clustered and its adaptive reaction to workload changes. With workloads based on the real-world topologies, T-Cache detects 43-70% of the inconsistencies and increases the rate of consistent transactions by 33-58%.Comment: Ittay Eyal, Ken Birman, Robbert van Renesse, "Cache Serializability: Reducing Inconsistency in Edge Transactions," Distributed Computing Systems (ICDCS), IEEE 35th International Conference on, June~29 2015--July~2 201

An analysis of acceptance policies for blockchain transactions

The standard acceptance policy for a cryptocurrency transaction at most exchanges is to wait until the transaction is placed in the blockchain and followed by a certain number of blocks. However, as noted by Sompolinsky and Zohar [16], the amount of time for blocks to arrive should also be taken into account as it affects the probability of double spending. Specifically, they propose a dynamic policy for transaction acceptance that depends on both the number of confirmations and the amount of time since transaction broadcast. In this work we study the implications of using such a policy compared with the standard option that ignores block timing information. Using an exact expression for the probability of double spend, via numerical results, we analyze time to transaction acceptance (performance) as well as the time and cost to perform a double spend attack (security). We show that while expected time required for transaction acceptance is improved using a dynamic policy, the time and cost to perform a double spend attack for a particular transaction is reduced.First author draf

Safe Permissionless Consensus

Nakamoto\u27s consensus protocol works in a permissionless model, where nodes can join and leave without notice. However, it guarantees agreement only probabilistically. Is this weaker guarantee a necessary concession to the severe demands of supporting a permissionless model? This paper shows that, at least in a benign failure model, it is not. It presents Sandglass, the first permissionless consensus algorithm that guarantees deterministic agreement and termination with probability 1 under general omission failures. Like Nakamoto, Sandglass adopts a hybrid synchronous communication model, where, at all times, a majority of nodes (though their number is unknown) are correct and synchronously connected, and allows nodes to join and leave at any time