Ittay Eyal

Hongyin Chen, Yubin Ke, Xiaotie Deng et al.

Smart contracts, the stateful programs running on blockchains, often rely on reports. Publishers are paid to publish these reports on the blockchain. Designing protocols that incentivize timely reporting is the prevalent reporting problem. But existing solutions face a security-performance trade-off: Relying on a small set of trusted publishers introduces centralization risks, while allowing open publication results in an excessive number of reports on the blockchain. We identify the root cause of this trade-off to be the standard symmetric reward design, which treats all reports equally. We prove that no symmetric-reward mechanism can overcome the trade-off. We present Personal Random Rewards for Reporting (Prrr), a protocol that assigns random heterogeneous values to reports. We call this novel mechanism-design concept Ex-Ante Synthetic Asymmetry. To the best of our knowledge, Prrr is the first game-theoretic mechanism (in any context) that deliberately forms participant asymmetry. Prrr employs a second-price-style settlement to allocate rewards, ensuring incentive compatibility and achieving both security and efficiency. Following the protocol constitutes a Subgame-Perfect Nash Equilibrium, robust against collusion and Sybil attacks. Prrr is applicable to numerous smart contracts that rely on timely reports.

Ali Farahbakhsh, Giuliano Losa, Youer Pu et al.

Permissionless blockchains achieve consensus while allowing unknown nodes to join and leave the system at any time. They typically come in two flavors: proof of work (PoW) and proof of stake (PoS), and both are vulnerable to attacks. PoS protocols suffer from long-range attacks, wherein attackers alter execution history at little cost, and PoW protocols are vulnerable to attackers with enough computational power to subvert execution history. PoS protocols respond by relying on external mechanisms like social consensus; PoW protocols either fall back to probabilistic guarantees, or are slow. We present Sieve-MMR, the first fully-permissionless protocol with deterministic security and constant expected latency that does not rely on external mechanisms. We obtain Sieve-MMR by porting a PoS protocol (MMR) to the PoW setting. From MMR we inherit constant expected latency and deterministic security, and proof-of-work gives us resilience against long-range attacks. The main challenge to porting MMR to the PoW setting is what we call time-travel attacks, where attackers use PoWs generated in the distant past to increase their perceived PoW power in the present. We respond by proposing Sieve, a novel algorithm that implements a new broadcast primitive we dub time-travel-resilient broadcast (TTRB). Sieve relies on a black-box, deterministic PoW primitive to implement TTRB, which we use as the messaging layer for MMR.

Marwa Mouallem, Lorenz Breidenbach, Ittay Eyal et al.

Smart contracts are stateful programs deployed on blockchains; they secure over a trillion dollars in transaction value per year. High-stakes smart contracts often rely on timely alerts about external events, but prior work has not analyzed their resilience to an attacker suppressing alerts via bribery. We formalize this challenge in a cryptoeconomic setting as the \emph{alerting problem}, giving rise to a game between a bribing adversary and~$n$ rational participants, who pay a penalty if they are caught deviating from the protocol. We establish a quadratic, i.e.,~$O(n^2)$, upper bound, whereas a straightforward alerting protocol only achieves~$O(n)$ bribery cost. We present a \emph{simultaneous game} that asymptotically achieves the quadratic upper bound and thus asymptotically-optimal bribery resistance. We then present two protocols that implement our simultaneous game: The first leverages a strong network synchrony assumption. The second relaxes this strong assumption and instead takes advantage of trusted hardware and blockchain proof-of-publication to establish a timed commitment scheme. These two protocols are constant-time but incur a linear storage overhead on the blockchain. We analyze a third, \emph{sequential alerting} protocol that optimistically incurs no on-chain storage overhead, at the expense of~$O(n)$ worst-case execution time. All three protocols achieve asymptotically-optimal bribery costs, but with different resource and performance tradeoffs. Together, they illuminate a rich design space for practical solutions to the alerting problem.

Uri Kirstein, Shelly Grossman, Michael Mirkin et al.

An attacker that gains access to a cryptocurrency user's private keys can perform any operation in her stead. Due to the decentralized nature of most cryptocurrencies, no entity can revert those operations. This is a central challenge for decentralized systems, illustrated by numerous high-profile heists. Vault contracts reduce this risk by introducing artificial delay on operations, allowing abortion by the contract owner during the delay. However, the theft of a key still renders the vault unusable and puts funds at risk. We introduce Phoenix, a novel contract architecture that allows the user to restore its security properties after key loss. Phoenix takes advantage of users' ability to store keys in easily-available but less secure storage (tier-two) as well as more secure storage that is harder to access (tier-one). Unlike previous solutions, the user can restore Phoenix security after the theft of tier-two keys and does not lose funds despite losing keys in either tier. Phoenix also introduces a mechanism to reduce the damage an attacker can cause in case of a tier-one compromise. We formally specify Phoenix's required behavior and provide a prototype implementation of Phoenix as an Ethereum contract. Since such an implementation is highly sensitive and vulnerable to subtle bugs, we apply a formal verification tool to prove specific code properties and identify faults. We highlight a bug identified by the tool that could be exploited by an attacker to compromise Phoenix. After fixing the bug, the tool proved the low-level executable code's correctness.

Roi Bar-Zur, Ittay Eyal, Aviv Tamar

A proof of work (PoW) blockchain protocol distributes rewards to its participants, called miners, according to their share of the total computational power. Sufficiently large miners can perform selfish mining - deviate from the protocol to gain more than their fair share. Such systems are thus secure if all miners are smaller than a threshold size so their best response is following the protocol. To find the threshold, one has to identify the optimal strategy for miners of different sizes, i.e., solve a Markov Decision Process (MDP). However, because of the PoW difficulty adjustment mechanism, the miners' utility is a non-linear ratio function. We therefore call this an Average Reward Ratio (ARR) MDP. Sapirshtein et al.\ were the first to solve ARR MDPs by solving a series of standard MDPs that converge to the ARR MDP solution. In this work, we present a novel technique for solving an ARR MDP by solving a single standard MDP. The crux of our approach is to augment the MDP such that it terminates randomly, within an expected number of rounds. We call this Probabilistic Termination Optimization (PTO), and the technique applies to any MDP whose utility is a ratio function. We bound the approximation error of PTO - it is inversely proportional to the expected number of rounds before termination, a parameter that we control. Empirically, PTO's complexity is an order of magnitude lower than the state of the art. PTO can be easily applied to different blockchains. We use it to tighten the bound on the threshold for selfish mining in Ethereum.

Itay Tsabary, Matan Yechieli, Alex Manuskin et al.

Smart Contracts and transactions allow users to implement elaborate constructions on cryptocurrency blockchains like Bitcoin and Ethereum. Many of these constructions, including operational payment channels and atomic swaps, use a building block called Hashed Time-Locked Contract (HTLC). In this work, we distill from HTLC a specification (HTLC-Spec), and present an implementation called Mutual-Assured-Destruction Hashed Time-Locked Contract (MAD-HTLC). MAD-HTLC employs a novel approach of utilizing the existing blockchain operators, called miners, as part of the design. If a user misbehaves, MAD-HTLC incentivizes the miners to confiscate all her funds. We prove MAD-HTLC's security using the UC framework and game-theoretic analysis. We demonstrate MAD-HTLC's efficacy and analyze its overhead by instantiating it on Bitcoin's and Ethereum's operational blockchains. Notably, current miner software makes only little effort to optimize revenue, since the advantage is relatively small. However, as the demand grows and other revenue components shrink, miners are more motivated to fully optimize their fund intake. By patching the standard Bitcoin client, we demonstrate such optimization is easy to implement, making the miners natural enforcers of MAD-HTLC. Finally, we extend previous results regarding HTLC vulnerability to bribery attacks. An attacker can incentivize miners to prefer her transactions by offering high transaction fees. We demonstrate this attack can be easily implemented by patching the Bitcoin client, and use game-theoretic tools to qualitatively tighten the known cost bound of such bribery attacks in presence of rational miners. We identify bribe opportunities occurring on the Bitcoin and Ethereum main networks where a few dollars bribe could yield tens of thousands of dollars in reward (e.g., \$2 for over \$25K).

Yael Doweck, Ittay Eyal

The problem of obtaining secret commitments from multiple parties and revealing them after a certain time is useful for sealed-bid auctions, games, and other applications. Existing solutions, dating back to Rivest, Shamir and Wagner, either do not scale or rely on synchrony for the commitment phase and trust of $t/n$ parties. We formalize the problem of implementing such commitments with a probabilistic delay and without the aforementioned assumptions as Multi-Party Timed Commitments (MPTC) and present a solution -- the Time-Capsule protocol. Like previous approaches, Time Capsule forms a puzzle whose solution reveals the committed values. But unlike previous solutions, no party has an advantage in solving the puzzle, and individual commitments cannot be revealed before the entire set is committed. A particular application of MPTC realizes an advancement in the study of decentralized systems. The state of the art in decentralized systems is manifested in blockchain systems that utilize Proof of Work to achieve censorship resistance. However, they are still vulnerable to frontrunning, an issue that is plaguing operational systems. By adapting Time Capsule, we allow it to be used for Proof of Work, preventing frontrunning by system operators and tuning the puzzle difficulty using the blockchain mechanism.

Michael Mirkin, Yan Ji, Jonathan Pang et al.

Proof-of-work (PoW) cryptocurrency blockchains like Bitcoin secure vast amounts of money. Their operators, called miners, expend resources to generate blocks and receive monetary rewards for their effort. Blockchains are, in principle, attractive targets for Denial-of-Service (DoS) attacks: There is fierce competition among coins, as well as potential gains from short selling. Classical DoS attacks, however, typically target a few servers and cannot scale to systems with many nodes. There have been no successful DoS attacks to date against prominent cryptocurrencies. We present Blockchain DoS (BDoS), the first incentive-based DoS attack that targets PoW cryptocurrencies. Unlike classical DoS, BDoS targets the system's mechanism design: It exploits the reward mechanism to discourage miner participation. Previous DoS attacks against PoW blockchains require an adversary's mining power to match that of all other miners. In contrast, BDoS can cause a blockchain to grind to a halt with significantly fewer resources, e.g., 21% as of March 2020 in Bitcoin, according to our empirical study. We find that Bitcoin's vulnerability to BDoS increases rapidly as the mining industry matures and profitability drops. BDoS differs from known attacks like Selfish Mining in its aim not to increase an adversary's revenue, but to disrupt the system. Although it bears some algorithmic similarity to those attacks, it introduces a new adversarial model, goals, algorithm, and game-theoretic analysis. Beyond its direct implications for operational blockchains, BDoS introduces the novel idea that an adversary can manipulate miners' incentives by proving the existence of blocks without actually publishing them.

Itay Tsabary, Alexander Spiegelman, Ittay Eyal

Proof of Work (PoW) is a Sybil-deterrence security mechanism. It introduces an external cost to a system by requiring computational effort to perform actions. However, since its inception, a central challenge was to tune this cost. Initial designs for deterring spam email and DoS attacks applied overhead equally to honest participants and attackers. Requiring too little effort did not deter attacks, whereas too much encumbered honest participation. This might be the reason it was never widely adopted. Nakamoto overcame this trade-off in Bitcoin by distinguishing desired from malicious behavior and introducing internal rewards for the former. This solution gained popularity in securing cryptocurrencies and using the virtual internally-minted tokens for rewards. However, in existing blockchain protocols the internal rewards fund (almost) the same value of external expenses. Thus, as the token value soars, so does the PoW expenditure. Bitcoin PoW, for example, already expends as much electricity as Colombia or Switzerland. This amount of resource-guzzling is unsustainable and hinders even wider adoption of these systems. In this work we present Hybrid Expenditure Blockchain (HEB), a novel PoW mechanism. HEB is a generalization of Nakamoto's protocol that enables tuning the external expenditure by introducing a complementary internal-expenditure mechanism. Thus, for the first time, HEB decouples external expenditure from the reward value. We show a practical parameter choice by which HEB requires significantly less external consumption compare to Nakamoto's protocol, its resilience against rational attackers is similar, and it retains the decentralized and permissionless nature of the system. Taking the Bitcoin ecosystem as an example, HEB cuts the electricity consumption by half.

Itay Tsabary, Ittay Eyal

Blockchain-based cryptocurrencies secure a decentralized consensus protocol by incentives. The protocol participants, called miners, generate (mine) a series of blocks, each containing monetary transactions created by system users. As incentive for participation, miners receive newly minted currency and transaction fees paid by transaction creators. Blockchain bandwidth limits lead users to pay increasing fees in order to prioritize their transactions. However, most prior work focused on models where fees are negligible. In a notable exception, Carlsten et al. postulated in CCS'16 that if incentives come only from fees then a mining gap would form~--- miners would avoid mining when the available fees are insufficient. In this work, we analyze cryptocurrency security in realistic settings, taking into account all elements of expenses and rewards. To study when gaps form, we analyze the system as a game we call \emph{the gap game}. We analyze the game with a combination of symbolic and numeric analysis tools in a wide range of scenarios. Our analysis confirms Carlsten et al.'s postulate; indeed, we show that gaps form well before fees are the only incentive, and analyze the implications on security. Perhaps surprisingly, we show that different miners choose different gap sizes to optimize their utility, even when their operating costs are identical. Alarmingly, we see that the system incentivizes large miner coalitions, reducing system decentralization. We describe the required conditions to avoid the incentive misalignment, providing guidelines for future cryptocurrency design.

Adem Efe Gencer, Soumya Basu, Ittay Eyal et al.

Blockchain-based cryptocurrencies have demonstrated how to securely implement traditionally centralized systems, such as currencies, in a decentralized fashion. However, there have been few measurement studies on the level of decentralization they achieve in practice. We present a measurement study on various decentralization metrics of two of the leading cryptocurrencies with the largest market capitalization and user base, Bitcoin and Ethereum. We investigate the extent of decentralization by measuring the network resources of nodes and the interconnection among them, the protocol requirements affecting the operation of nodes, and the robustness of the two systems against attacks. In particular, we adapted existing internet measurement techniques and used the Falcon Relay Network as a novel measurement tool to obtain our data. We discovered that neither Bitcoin nor Ethereum has strictly better properties than the other. We also provide concrete suggestions for improving both systems.

Joshua Lind, Oded Naor, Ittay Eyal et al.

Blockchains such as Bitcoin and Ethereum execute payment transactions securely, but their performance is limited by the need for global consensus. Payment networks overcome this limitation through off-chain transactions. Instead of writing to the blockchain for each transaction, they only settle the final payment balances with the underlying blockchain. When executing off-chain transactions in current payment networks, parties must access the blockchain within bounded time to detect misbehaving parties that deviate from the protocol. This opens a window for attacks in which a malicious party can steal funds by deliberately delaying other parties' blockchain access and prevents parties from using payment networks when disconnected from the blockchain. We present Teechain, the first layer-two payment network that executes off-chain transactions asynchronously with respect to the underlying blockchain. To prevent parties from misbehaving, Teechain uses treasuries, protected by hardware trusted execution environments (TEEs), to establish off-chain payment channels between parties. Treasuries maintain collateral funds and can exchange transactions efficiently and securely, without interacting with the underlying blockchain. To mitigate against treasury failures and to avoid having to trust all TEEs, Teechain replicates the state of treasuries using committee chains, a new variant of chain replication with threshold secret sharing. Teechain achieves at least a 33x higher transaction throughput than the state-of-the-art Lightning payment network. A 30-machine Teechain deployment can handle over 1 million Bitcoin transactions per second.

Joshua Lind, Ittay Eyal, Peter Pietzuch et al.

Blockchain protocols are inherently limited in transaction throughput and latency. Recent efforts to address performance and scale blockchains have focused on off-chain payment channels. While such channels can achieve low latency and high throughput, deploying them securely on top of the Bitcoin blockchain has been difficult, partly because building a secure implementation requires changes to the underlying protocol and the ecosystem. We present Teechan, a full-duplex payment channel framework that exploits trusted execution environments. Teechan can be deployed securely on the existing Bitcoin blockchain without having to modify the protocol. It: (i) achieves a higher transaction throughput and lower transaction latency than prior solutions; (ii) enables unlimited full-duplex payments as long as the balance does not exceed the channel's credit; (iii) requires only a single message to be sent per payment in any direction; and (iv) places at most two transactions on the blockchain under any execution scenario. We have built and deployed the Teechan framework using Intel SGX on the Bitcoin network. Our experiments show that, not counting network latencies, Teechan can achieve 2,480 transactions per second on a single channel, with sub-millisecond latencies.

Ittay Eyal, Adem Efe Gencer, Emin Gun Sirer et al.

Cryptocurrencies, based on and led by Bitcoin, have shown promise as infrastructure for pseudonymous online payments, cheap remittance, trustless digital asset exchange, and smart contracts. However, Bitcoin-derived blockchain protocols have inherent scalability limits that trade-off between throughput and latency and withhold the realization of this potential. This paper presents Bitcoin-NG, a new blockchain protocol designed to scale. Based on Bitcoin's blockchain protocol, Bitcoin-NG is Byzantine fault tolerant, is robust to extreme churn, and shares the same trust model obviating qualitative changes to the ecosystem. In addition to Bitcoin-NG, we introduce several novel metrics of interest in quantifying the security and efficiency of Bitcoin-like blockchain protocols. We implement Bitcoin-NG and perform large-scale experiments at 15% the size of the operational Bitcoin system, using unchanged clients of both protocols. These experiments demonstrate that Bitcoin-NG scales optimally, with bandwidth limited only by the capacity of the individual nodes and latency limited only by the propagation time of the network.

Ittay Eyal

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.

Ittay Eyal, Emin Gun Sirer

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.