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 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.

NANOZK introduces a novel, highly efficient zero-knowledge proof system that allows users to cryptographically verify that the output of a large language model (LLM) was generated by a specific, claim…

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…

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…

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…

The paper introduces a four-stage structural dependency analysis hierarchy that enables scalable, sound first-order masking verification for large, production-level post-quantum cryptographic accelera…

The paper proposes Hermes Seal, a zk-SNARK framework that enables autonomous vehicles to generate cryptographic proofs of their internal computations and perceptions without revealing sensitive propri…

KVerus is a retrieval-augmented system that significantly improves the scalability and resilience of formal verification for Rust code by managing complex cross-module dependencies and adapting to cod…

The paper introduces AlphaEvolve, an evolutionary search framework that automates the optimization of Fully Homomorphic Encryption (FHE) kernels on TPUs, achieving significant speedups over human-engi…

The paper introduces a framework, PD-FHC, that allows users to outsource Boolean computations to an untrusted cloud while guaranteeing both computational privacy and plausible deniability against coer…

This paper provides the first unified, security-focused survey that rigorously maps Layer-2 (L2) blockchain architecture to its underlying cryptographic security assumptions.

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.

The paper proposes a federated formal verification architecture that treats verification as a polyglot proof system, successfully validating it on complex production subsystems like a Raft consensus m…

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…

The paper provides the first machine-checked universal proof, using ring theory, that value-independence implies identical marginal distributions for arithmetic masking, thereby extending the verifica…

The paper proposes a co-design paradigm, 'Meeting in the Middle,' to make Fully Homomorphic Encryption (FHE) practical for AI inference by optimizing both the cryptographic schemes and the underlying…

EncFormer is a novel two-party framework that significantly improves the efficiency and scalability of private Transformer inference by optimizing the combination of Fully Homomorphic Encryption (FHE)…

The paper introduces PoSME, a cryptographic primitive that enforces strict sequential memory execution by chaining data-dependent writes, providing verifiable delay and authorship attestation.