arXiv subjects

Roi Bar-Zur

Publications and source records attributed to Roi Bar-Zur.

5 recordsLinked to original sources

arXiv2026

Crypto x AI, AI x Crypto: A Survey

The intersection of crypto x AI is spawning papers, products, online posts, and companies. All the surrounding buzz, though, obscures what exactly has been done, what the opportunities and challenges are, and what open questions deserve attention. This survey paper asks what AI can do for blockchain-based technologies (broadly construed as "crypto") (crypto x AI), and vice versa (AI x crypto). We systematize existing work, summarize key takeaways, highlight open research questions, and offer a perspective on pervasive industry misconceptions, concluding that AI and crypto are still in the very early stages of meaningful integration.

cs.CR↗

arXiv2025

MAD-DAG: Protecting Blockchain Consensus from MEV

Blockchain security is threatened by selfish mining, where a miner (operator) deviates from the protocol to increase their revenue. Selfish mining is exacerbated by adverse conditions: rushing (network propagation advantage for the selfish miner), varying block rewards due to block contents, called miner extractable value (MEV), and petty-compliant miners who accept bribes from the selfish miner. The state-of-the-art selfish-mining-resistant blockchain protocol, Colordag, does not treat these adverse conditions and was proven secure only when its latency is impractically high. We present MAD-DAG, Mutually-Assured-Destruction Directed-Acyclic-Graph, the first practical protocol to counter selfish mining under adverse conditions. MAD-DAG achieves this thanks to its novel ledger function, which discards the contents of equal-length chains competing to be the longest. We analyze selfish mining in both Colordag and MAD-DAG by modeling a rational miner using a Markov Decision Process (MDP). We obtain a tractable model for both by developing conservative reward rules that favor the selfish miner to yield an upper bound on selfish mining revenue. To the best of our knowledge, this is the first tractable model of selfish mining in a practical DAG-based blockchain. This enables us to obtain a lower bound on the security threshold, the minimum fraction of computational power a miner needs in order to profit from selfish mining. MAD-DAG withstands adverse conditions under which Colordag and Bitcoin fail, while otherwise maintaining comparable security. For example, with petty-compliant miners and high levels of block reward variability, MAD-DAG's security threshold ranges from 11% to 31%, whereas both Colordag and Bitcoin achieve 0% for all levels.

cs.CR↗

arXiv2025

Elastic Restaking Networks

Many blockchain-based decentralized services require their validators (operators) to deposit stake (collateral), which is forfeited (slashed) if they misbehave. Restaking networks let validators secure multiple services by reusing stake. These networks have quickly gained traction, leveraging over \$20 billion in stake. However, restaking introduces a new attack vector where validators can coordinate to misbehave across multiple services simultaneously, extracting digital assets while forfeiting their stake only once. Previous work focused either on preventing coordinated misbehavior or on protecting services if all other services are Byzantine and might unjustly cause slashing due to bugs or malice. The first model overlooks how a single Byzantine service can collapse the network, while the second ignores shared-stake benefits. To bridge the gap, we analyze the system as a strategic game of coordinated misbehavior, when a given fraction of the services are Byzantine. We introduce elastic restaking networks, where validators can allocate portions of their stake that may cumulatively exceed their total stake, and when allocations are lost, the remaining stake stretches to cover remaining allocations. We show that elastic networks exhibit superior robustness compared to previous approaches, and demonstrate a synergistic effect where an elastic restaking network enhances its blockchain's security, contrary to community concerns of an opposite effect in existing networks. We then design incentives for tuning validators' allocations. Our elastic restaking system and incentive design have immediate practical implications for deployed restaking networks.

cs.GT↗

arXiv2025

Aegis: Tethering a Blockchain with Primary-Chain Stake

Blockchains implement decentralized monetary systems and applications. Recent advancements enable what we call tethering a blockchain to a primary blockchain, securing the tethered chain by nodes that post primary-chain tokens as collateral. The collateral ensures nodes behave as intended, until they withdraw it. Unlike a Proof of Stake blockchain which uses its own token as collateral, using primary-chain tokens shields the tethered chain from the volatility of its own token. State-of-the-art tethered blockchains either rely on centralization, or make extreme assumptions: that all communication is synchronous, that operators remain correct even post-withdrawal, or that withdrawals can be indefinitely delayed by tethered-chain failures. We prove that with partial synchrony, there is no solution to the problem. However, under the standard assumptions that communication with the primary chain is synchronous and communication among the tethered chain nodes is partially synchronous, there is a solution. We present a tethered-chain protocol called Aegis. Aegis uses references from its blocks to primary blocks to define committees, checkpoints on the primary chain to perpetuate decisions, and resets to establish new committees when previous ones become obsolete. It ensures safety at all times and rapid progress when latency among Aegis nodes is low.

cs.DC↗

arXiv2020

Efficient MDP Analysis for Selfish-Mining in Blockchains

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.

cs.CR↗