Formalizing Maximal Extractable Value for Blockchain Security Proofs
This research establishes a formal theory of Maximal Extractable Value (MEV) through an abstract blockchain model, enabling rigorous security proofs against economic attacks.
ZKPoT Consensus Secures Federated Learning Privacy and Efficiency
A novel ZKPoT consensus leverages zk-SNARKs to privately validate federated learning contributions, significantly boosting security and efficiency.
LLMs Automate Smart Contract Formal Verification Property Generation
A novel system leverages large language models and retrieval-augmented generation to automate smart contract property creation, enhancing security and accessibility.
Revelation Mechanisms for Trustworthy Blockchain Consensus
This research introduces revelation mechanisms within Proof-of-Stake protocols, fundamentally addressing consensus disputes by incentivizing truthful block proposals.
Formalizing Maximal Extractable Value: A Foundational Theory for Blockchain Security
This theory formally defines Maximal Extractable Value, offering a robust framework for proving smart contract security and clarifying adversarial extraction in blockchains.
Game Theory Models MEV Dynamics and Mitigation Strategies
This research formally models MEV as a multi-stage game, revealing competitive dynamics that degrade welfare and quantifies mitigation through commit-reveal schemes.
THORChain Co-Founder Wallet Compromised via Social Engineering
A sophisticated social engineering campaign led to the compromise of a prominent individual's private key, resulting in a seven-figure asset drain.
Monero Suffers 18-Block Reorganization, Exposing Double-Spend Risk
An unprecedented 18-block chain reorganization on Monero's mainnet demonstrates critical vulnerabilities to adversarial block withholding, threatening transaction finality.
Execution Tickets: Protocolizing MEV for Equitable Value Distribution
A novel ticketing mechanism aims to integrate Maximal Extractable Value directly into the Ethereum protocol, fostering fairer distribution and network robustness.