Formalizing MEV with Adversarial Knowledge Enables Provable Security
This abstract model defines Maximal Extractable Value via adversarial knowledge, providing the foundational theory for provable security against economic attacks.
Formalizing MEV Theory for Provably Secure Blockchain Architectures
This research establishes a foundational mathematical framework for Maximal Extractable Value, enabling rigorous analysis and provably secure defenses against economic exploitation.
Formalizing MEV: Rigorous Model for Provably Secure Blockchain Architectures
This research introduces a formal, abstract model for Maximal Extractable Value, enabling systematic analysis and the development of provably secure blockchain protocols.
Formalizing MEV Theory for Provable Blockchain Security
A new formal theory for Maximal Extractable Value offers a robust framework to understand and secure blockchain systems against economic attacks.
Batch Processing Eliminates MEV in Automated Market Makers
This research introduces a novel batch-processing mechanism for Automated Market Makers, fundamentally mitigating Miner Extractable Value and fostering equitable transaction execution.
Formalizing MEV for Provable Security in Blockchain Protocols
A new formal theory of MEV provides provable security against economic attacks, differentiating beneficial from malicious value extraction in blockchain protocols.
LLM-driven Property Generation Elevates Smart Contract Formal Verification
This research introduces PropertyGPT, an AI-powered system that automates comprehensive property generation, overcoming a critical bottleneck in smart contract formal verification.
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.
