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…

The paper introduces DPrivBench, a new benchmark to test whether large language models (LLMs) can automate the complex reasoning required to verify differential privacy guarantees for algorithms.

The paper proposes COD-ssi, a novel framework that achieves mutual privacy in Self-Sovereign Identity (SSI) credential exchanges, ensuring that neither the Holder nor the Verifier can learn unnecessar…

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…

SILMARILS presents a quantum-secure, information-theoretic designated-verifier (DV) signature scheme built on a minimal algebraic core, suitable for lightweight blockchain authentication.

The paper proposes a trust-boundary architecture using Lean 4 to verify the deterministic structured computations surrounding LLM pipelines, providing verifiable certificates for high-stakes deploymen…

The paper introduces Zero-Run privacy auditing, a post-hoc framework that allows for practical differential privacy evaluation of large, deployed models without requiring retraining or controlled data…

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…

This paper proposes a multi-layered defense strategy combining pre-output monitoring, calibrated canary detection, and cumulative information-flow tracking to prevent LLM agents from exfiltrating sens…

This paper introduces ShannonProver, an agentic framework that automates cryptographic proofs in EasyCrypt, allowing for scalable proof verification.

This paper introduces Code-Poisoning Property Inference Attack (CPPIA), the first code-level Property Inference Attack (PIA) for leaking privacy from ML models trained on private data, overcoming limi…

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 proposes a new approach for cryptographically verifiable agent authorization, formalizing it as a relation that binds an agent principal, a request, an execution context, and policy satisfa…

The paper introduces AgentSecBench, a security evaluation framework that measures prompt injection, privacy leakage, and tool-use integrity in LLM agents by defining formal security games and testing…

The paper introduces an efficient, lightweight LLM framework for smart contract auditing that decouples the audit process into multiple components, achieving high accuracy while significantly reducing…

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 proposes RPSG, a method that uses private seeds and differential privacy to generate highly realistic and strongly privacy-preserving synthetic data replicas of private text for LLMs.

VeriX-Anon is a multi-layered framework that provides mathematically verifiable assurance that outsourced data anonymization (k-anonymization) was executed correctly, achieving high detection rates ag…

The paper reverse-engineers Apple's Private Cloud Compute (PCC) implementation to independently benchmark its model and evaluate its privacy claims, addressing the lack of transparency in Apple's syst…