Protocol-Native MEV Brokering Enhances Blockchain Economic Fairness
A novel ticketing mechanism directly integrates Maximal Extractable Value distribution into the Ethereum protocol, fundamentally reshaping network economics.
Formalizing MEV for Blockchain Security Proofs
This research establishes a formal theory of Maximal Extractable Value, providing a foundational model for analyzing and proving blockchain security against economic attacks.
Shibarium Bridge Compromised via Validator Key Exploitation and Flash Loan
A sophisticated flash loan attack on Shibarium's bridge exploited validator key control, enabling the illicit drainage of multi-million dollar assets.
ZKPoT: Private, Efficient Consensus for Federated Learning Blockchains
A novel Zero-Knowledge Proof of Training consensus validates federated learning contributions privately, overcoming traditional blockchain inefficiencies and privacy risks.
Formalizing MEV: A Foundational Theory for Blockchain Security
Researchers introduce a formal theory of Maximal Extractable Value, providing a rigorous framework to understand and counter economic attacks in decentralized systems.
Game Theory Quantifies MEV Harm, Proposes Mitigation Strategies
This research formalizes MEV extraction as a multi-stage game, revealing systemic welfare losses and proposing cryptographic mechanisms to restore market fairness.
Formalizing MEV Theory for Blockchain Security and Mechanism Design
This paper establishes a rigorous, abstract framework for Maximal Extractable Value, enabling systematic analysis and robust defenses against economic exploits in decentralized systems.
Formal Verification Properties for Smart Contract Security
A novel framework defines universal properties—Validity, Liquidity, Fidelity—to rigorously verify smart contract behavior, fundamentally enhancing blockchain security.
Shibarium Bridge Suffers Flash Loan Validator Key Compromise
A flash loan attack manipulated Shibarium's validator consensus, enabling unauthorized asset siphoning and exposing critical governance vulnerabilities.
