The paper proposes a revocation-ready key management layer for blockchain-based IoT data sharing that replaces online key release with ciphertext key publication, enabling local, policy-based decrypti…

This paper analyzes digital privacy risks in IoT ecosystems, proposing a comprehensive framework (AURA-IoT) and taxonomy to mitigate threats using advanced privacy-enhancing technologies.

The paper proposes a novel data transformation framework that creates semantically rich, privacy-preserving numeric views of EHR data, enabling large-scale research while provably breaking patient lin…

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…

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 provides the first comprehensive review of threats and defenses specifically targeting on-device AI inference, revealing a significant imbalance where certain attack types, like adversarial…

The paper introduces APLiance, a novel ABAC framework that models privacy policies as access requests and checks their compliance against legal requirements by mapping law sections to ABAC rules.

This paper analyzes Bitcoin's new V2 P2P transport protocol, demonstrating that while it fixes known vulnerabilities, attackers can still execute conceptual attacks like message identification via pay…

The paper proposes the User Data Sharing System (UDSS), a hardware-anchored middleware that securely manages PII exchange across diverse consumer electronics devices, significantly reducing onboarding…

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…

The paper proposes S3CDM, a secret-sharing-scheme-based model that enhances cyberattack detection, particularly against insider threats, by distributing authentication secrets across multiple network…

This paper conducts an extensive microbenchmark study to characterize the performance of core cryptographic workloads across various cloud services, architectures, and programming languages, identifyi…

This paper proposes and demonstrates a method to secure high-performance RDMA data transfers by implementing AES-128 encryption directly within a programmable network switch, maintaining high throughp…

The paper introduces PriSrv+, an advanced service discovery protocol that significantly enhances privacy, usability, and efficiency in wireless networks through a novel matchmaking encryption scheme c…

The paper proposes and validates a privacy-preserving framework using Homomorphic Encryption (HE) to train and run Machine Learning models on sensitive data while keeping it encrypted throughout the e…

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…

The paper addresses the over-reliance on GDPR in digital privacy research by systematically normalizing heterogeneous global data protection laws into a unified, data-lifecycle-aligned abstraction.

The paper introduces $I$-$(OT)^2$, a novel base 1-out-of-2 Oblivious Transfer (OT) protocol designed to minimize computation and interaction for resource-constrained IoT devices.

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…

The paper introduces Beyond Zero, a new security paradigm that moves beyond traditional zero trust by performing per-resource and method access decisions at machine speed to secure the enterprise agai…