Explore the foundational ideas of crypto. The Research category breaks down cutting-edge whitepapers, academic studies, and the technical theories shaping the future of blockchain technology.
This research introduces a novel OR-aggregation technique, enabling constant-size zero-knowledge proofs for set membership in resource-constrained IoT blockchain environments.
This research introduces "Execution Tickets," a novel mechanism to integrate and redistribute Maximal Extractable Value directly within the Ethereum protocol, enhancing network fairness and security.
This research introduces novel proof systems and architectures that fundamentally scale zero-knowledge proofs, reducing server communication costs for privacy-preserving applications.
This research extends doubly efficient interactive proofs to arbitrary arithmetic circuits, achieving optimal linear prover time and succinct verification without requiring costly circuit layering.
Proof of Team Sprint transforms energy-intensive blockchain consensus into a collaborative effort, reducing environmental impact and enhancing network sustainability.
This research leverages game theory to model Maximal Extractable Value dynamics, proposing commit-reveal and threshold encryption mechanisms to enhance DeFi fairness.
This research establishes a rigorous theoretical framework for Maximal Extractable Value, enabling provably secure mitigation strategies for blockchain vulnerabilities.
This research synthesizes Zero-Knowledge Proof advancements, enabling secure information verification without revealing sensitive data, fundamentally reshaping digital privacy and trust.
This research introduces PropertyGPT, an AI-powered system that automates comprehensive property generation, overcoming a critical bottleneck in smart contract formal verification.
This survey demystifies the complex Zero-Knowledge Proof landscape, offering a critical evaluation of frameworks to accelerate practical application development.
This protocol embeds threshold encryption directly into consensus, eradicating MEV and enabling a new era of private, fair, and institution-ready decentralized applications.
A novel ticketing mechanism directly integrates Maximal Extractable Value distribution into the Ethereum protocol, fundamentally reshaping network economics.
This research establishes a formal theory of Maximal Extractable Value, providing a foundational model for analyzing and proving blockchain security against economic attacks.
This research introduces a novel Zero-Knowledge Proof of Training consensus, enabling privacy-preserving, high-performance validation of machine learning contributions on decentralized networks.
This research establishes a formal theory of Maximal Extractable Value, providing a robust framework for understanding and mitigating economic attacks on blockchains.
Zero-knowledge proofs revolutionize digital trust, allowing verifiable computation without data disclosure, unlocking new paradigms for privacy and scalability.
This research formalizes MEV extraction as a multi-stage game, revealing systemic welfare losses and proposing cryptographic mechanisms to restore market fairness.
This research introduces novel ZKP protocols, significantly improving proof generation speed to enable broader, more efficient privacy-preserving applications.
This paper establishes a rigorous, abstract framework for Maximal Extractable Value, enabling systematic analysis and robust defenses against economic exploits in decentralized systems.
This research introduces novel zero-knowledge proof systems that dramatically reduce server communication costs for private analytics and enhance distributed proof generation scalability, fundamentally improving the efficiency of privacy-preserving computations.
This research establishes a foundational framework for analyzing the economic security of blockchain consensus protocols, quantifying attack costs to enable more robust designs.
Proof of Team Sprint redefines blockchain consensus by replacing individual competition with collaborative cryptographic puzzle-solving, drastically reducing energy consumption.
This research establishes a precise framework for ensuring network progress and identifying faulty actors within dynamic blockchain environments, foundational for resilient protocol design.
This research introduces a suite of ZKP protocols that fundamentally overcome proof generation bottlenecks, enabling scalable and private computation for decentralized systems.
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