The paper demonstrates that passive motion traces recorded during a mobile selfie capture can serve as a measurable, low-friction auxiliary signal for enhancing both spoof screening and user identity…

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.

The paper proposes ChaRVoC, a novel Challenge-Response Voice Cancelable authentication system that enhances voice biometrics by integrating inherent voice features, secret keys, and dynamic challenges…

BioMoTouch is a multi-modal touch authentication framework that jointly models physiological contact structures (from capacitive screens) and behavioral motion dynamics (from inertial sensors) to achi…

A-Live is a passive liveness detection framework that uses subtle neuromuscular micro-motion signatures captured by commodity IMU sensors to distinguish human users from non-human agents with high acc…

The paper introduces DECKER, a domain-invariant framework that significantly improves cross-keyboard keystroke inference by normalizing device variations and leveraging linguistic context, demonstrati…

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 an Android-based middleware that enables visually impaired users to securely and independently perform mobile money transactions via voice commands, significantly improving accessib…

The paper introduces ArrythML, a highly efficient autoencoder-based TinyML model that enables accurate, low-power arrhythmia detection directly on resource-constrained embedded wearable devices.

The paper proposes Family-Grouped Hierarchical Federated Learning (Family-FL) combined with a highly optimized Tiny CNN-LSTM model to enable privacy-preserving ECG monitoring on ultra-resource-constra…

This paper introduces a systematic, privacy-preserving method using keystroke dynamics to robustly distinguish between human typing and automated HID injection attacks, independent of user identity.

This paper models PIN entry as a stochastic communication channel, proposing a probabilistic inference framework to quantify reliability loss and QoS degradation caused by partial information leakage.

STEP introduces a novel, black-box, retraining-free detector that profiles audio samples using dual perturbation branches to detect backdoor attacks by exploiting the characteristic instability of hid…

The paper proposes Asymmetric Phase Coding (APC), a training-free cryptographic audio watermarking scheme that achieves high extraction rates (97.5%-98.3%) across various real-world and adversarial at…

The paper proposes a Class-Aware Adaptive Differential Privacy (CA-ADP) framework integrated with a 3D CNN-BiLSTM architecture to significantly improve privacy-preserving fall detection performance co…

The paper proposes a graduated trust gating mechanism for IoT location verification that moves beyond binary decisions, allowing systems to dynamically escalate verification rigor based on signal inte…

Ciphera proposes a decentralized biometric identity framework that combines facial recognition with DIDs and VCs, achieving feasible sub-second verification while highlighting challenges in revocation…

The paper proposes a privacy-preserving system for crowd monitoring that counts individuals across different locations and time periods using face recognition without ever revealing personal identitie…

The paper proposes a RADIUS-based framework to maintain persistent device identity for Network Access Control (NAC) despite modern operating system MAC address randomization, ensuring regulatory compl…

This paper surveys information-theoretic approaches to secure Integrated Sensing and Communication (ISAC), providing a comprehensive review of models, security formulations, and fundamental limits.