The paper addresses the vulnerability of zero-knowledge proximity proofs in stateful systems by proposing Zairn-ZKP, a method that embeds operational context (like drop identity and policy version) di…

The paper proposes ZK-Flex, a flexible software-hardware co-designed framework that significantly accelerates Zero-Knowledge Proof (ZKP) generation by efficiently handling diverse polynomial and ellip…

The paper proposes ZK-Flex, a flexible software-hardware co-designed framework that significantly accelerates Zero-Knowledge Proof (ZKP) generation by efficiently handling diverse polynomial and ellip…

ZK-Value introduces a practical, scalable zero-knowledge system for calculating data valuations (Shapley values) in data marketplaces, significantly reducing proving time while maintaining high accura…

The paper proposes Agentic Witnessing, a TEE-enabled framework that allows external verifiers to audit the qualitative properties of private datasets by querying an LLM-based auditor without accessing…

The paper introduces Search-Bound Proximity Proofs (SBPP) to close an authorization provenance gap in encrypted geographic search by binding zero-knowledge proofs to specific search sessions for audit…

zk-X509 is a privacy-preserving identity system that uses zero-knowledge proofs to prove ownership of standard X.509 certificates on a public blockchain without revealing private keys or personal data…

The paper introduces a lightweight, sampling-based cryptographic protocol for verifiable AI inference that drastically reduces proving overhead from minutes to milliseconds by leveraging statistical p…

SS-ZKR is a novel, three-mechanism protocol that enables privacy-preserving, content-based semantic routing of agent payloads across organizational trust boundaries without requiring the intermediary…

SS-ZKR is a novel, three-mechanism protocol that enables privacy-preserving, content-based semantic routing of agent payloads across organizational trust boundaries without requiring the intermediary…

The paper introduces MORPH, a framework that reformulates Zero-Knowledge Proof (ZKP) computations to efficiently utilize AI ASICs like TPUs, achieving up to 10x higher throughput on NTT.

The paper proves that platform-deterministic inference is a necessary and sufficient condition for trustworthy AI, establishing that AI trust fundamentally relies on consistent arithmetic.

zkSBOM introduces a zero-knowledge mechanism for sharing Software Bills of Materials (SBOMs) that allows consumers to check for vulnerabilities without suppliers revealing the full, sensitive contents…

This paper systematically analyzes 48 studies on perception attacks against autonomous vehicles, revealing that the increasing reliance on multi-sensor fusion creates new, complex vulnerabilities that…

The paper presents a novel technology that uses zero-knowledge proofs to formally verify a software system's correctness against a public specification without revealing the system's internal details.

The paper proposes a lightweight Zero-Knowledge authentication protocol using QR codes, enhancing the Schnorr protocol with nonces and timestamps for secure, efficient, and replay-attack-resistant aut…

The paper introduces a reinforcement learning framework, inspired by AlphaZero, to automate and improve the proof search process within the Tamarin protocol analysis tool, resulting in shorter and mor…

The paper proposes a distributed, privacy-preserving monitoring architecture that uses secret-sharing to efficiently monitor systems with continuous state, overcoming the scalability issues of traditi…

Obscura is a novel, decentralized privacy protocol for the Algorand blockchain that achieves transaction anonymity using LSAG ring signatures, overcoming the limitations of existing zk-SNARK-based met…

The paper introduces a systematic, executable taxonomy of security properties to bridge the gap between theoretical security definitions and their practical implementation in formal verification tools…