Cryptography is the science of secure communication, employing mathematical algorithms to protect information and verify authenticity. It underpins the security of blockchain networks through hashing and digital signatures, and facilitates privacy via encryption. Its principles are vital for ensuring the integrity of transactions and the security of digital assets.
Context
News coverage of cryptography in the crypto space often highlights advancements in zero-knowledge proofs for enhanced privacy, the security implications of quantum computing on current cryptographic methods, and the development of more robust encryption techniques for digital asset protection.
A novel validated strong BFT model enables leader-based asynchronous consensus, reducing message complexity and achieving linear view changes for scalable blockchains.
A novel cryptographic primitive distributes signing authority across multiple parties, fundamentally mitigating single points of failure and bolstering decentralized system resilience.
This research introduces a novel batch-processing mechanism for Automated Market Makers, fundamentally mitigating Miner Extractable Value and fostering equitable transaction execution.
Secure Multi-Party Computation enables joint function computation on private data, fostering privacy and collaboration across decentralized systems and sensitive applications.
A novel system leverages large language models and retrieval-augmented generation to automate smart contract property creation, enhancing security and accessibility.
This research formally models Maximal Extractable Value dynamics, proving its systemic welfare costs, and proposes cryptographic mechanisms to mitigate its adverse effects on decentralized finance.
This research formalizes Maximal Extractable Value dynamics through a multi-stage game, revealing systemic inefficiencies and quantifying mitigation strategies.
This research establishes a universal, game-theoretic definition for Maximal Extractable Value, fundamentally reframing economic attacks within public blockchains for systematic mitigation.
This research formalizes Maximal Extractable Value, providing a rigorous framework for understanding and mitigating systemic blockchain vulnerabilities.
This research advances zero-knowledge proofs, offering new cryptographic designs to fundamentally improve privacy and scaling for decentralized systems.
This research establishes a formal theory of Maximal Extractable Value (MEV) through an abstract blockchain model, enabling rigorous security proofs against economic attacks.
The Ethereum Foundation's privacy roadmap redefines on-chain confidentiality, integrating advanced cryptographic primitives to secure transaction metadata and user interactions across the protocol stack.
This architectural evolution integrates end-to-end privacy across the Ethereum stack, establishing a foundational layer for confidential digital interactions and verifiable data integrity.
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