BIDO introduces a device-free, NIST AAL2-compliant biometric authentication standard that deterministically generates ephemeral ECDSA keys from live biometric measurements, eliminating the need for st…

The paper proposes a scalable, privacy-preserving framework for iris recognition using Fully Homomorphic Encryption (FHE), achieving accuracy comparable to cleartext while identifying the computationa…

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 introduces a novel, scalable, and provably secure biometric authentication system designed to authenticate millions of users against cloud databases without requiring auxiliary identifiers.

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 proposes bPk#, a distributed architecture for pseudonyms that enhances privacy and availability in national eID systems by delegating pseudonym computation rights to users and service provid…

This paper introduces a unified threat model and evaluation framework to systematically compare privacy-preserving techniques for distributed learning in IoT systems, highlighting the trade-off betwee…

The paper proposes and proves the security of a generic, full end-to-end credential revocation system for European Digital Identity Wallets, relying on a single server and secure channels.

This paper empirically evaluates the effectiveness of Differential Privacy (DP) against Membership Inference Attacks (MIAs) in Federated Learning, demonstrating that a stacking attack strategy can det…

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 introduces BSGS-Diagonal, a memory-efficient algorithm, and GPU-optimized kernels to significantly accelerate and reduce the resource overhead of encrypted face recognition using Fully Homom…

The paper proposes AgentDID, a decentralized framework using DIDs and verifiable credentials to provide trustless identity authentication and dynamic state verification for autonomous, self-managed AI…

The paper introduces $\pi$Creds, a novel system for generating privacy-preserving, decentralized verifiable credentials by leveraging LLM inference over authenticated data, significantly expanding the…

The paper proposes a canonical, end-to-end validation framework to ensure secure integration of Alternative Data Availability (AltDA) systems with Ethereum Layer 2s, demonstrating that L2 integration…

This paper provides a comprehensive, system-level comparison of MPC and FHE for Privacy-Preserving Machine Learning (PPML) across various models and environments, moving beyond single-metric latency a…

Intercloud proposes a decentralized economic network that achieves eventual consistency and security using a novel 'chilling-effect consensus' mechanism, eliminating the need for global coordination.

HadAgent introduces a decentralized AI serving system that replaces resource-intensive Proof-of-Work with Proof-of-Inference (PoI) to secure LLM agent operations and achieve fast, verifiable consensus…

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…

FedEDAuth is a lightweight, embedding-level authentication framework that enhances federated learning for counterfeit IC detection by identifying and filtering malicious participants before model aggr…

The paper introduces MolTrust, a production-deployed trust infrastructure built on W3C standards (VCs and DIDs) that provides a verifiable, multi-layered authorization framework for autonomous AI agen…