ECHO: Revealing Review-to-Submission Linkage in Anonymous Peer Review
Anonymous peer review protects reviewers from retaliation, yet reviewer anonymity may also be weakened by artifacts rele
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We revisit DM-RSA, an RSA variant that uses two independent moduli, whose original version was broken by Håstad's attack
Traffic cameras support useful analysis, but their outputs can reveal private information. Replacing images with text re
AI agents in containers act by opening network connections, and the text that drives them can be hostile. Controls place
Machine-learning (ML) malware detectors are known to be vulnerable to adversarial samples. Generative adversarial networ
This paper derives an exact attenuation formula for multivariate cross-moments under differential privacy achieved throu
Hidden randomized rounding couples the privacy loss of successive integer releases. We study a rational-feedback mechani
Statistical privacy audits are essential for verifying the theoretical privacy guarantees of differentially private (DP)
This study presents a 96-day longitudinal analysis of Secure Reliable Transport (SRT) protocol behavior in a production
Quantum machine-learning (QML) models are increasingly considered for security applications, yet their adversarial robus
Tactile perception is crucial for precise robotic manipulation, providing an important foundation for dexterous, closed-
The security guarantees of existing formally verified compilers for compartmentalized programs in unsafe languages like
As coding models and agent harnesses become more capable, reliable security verification is becoming a central bottlenec
The threat of quantum computers breaking classical cryptographic is accelerating the adoption of quantum- resistant cryp
Terminally ill patients generate extensive digital health data through hospital portals, physiological monitoring device
Secure aggregation enables a server to compute the sum of users' gradients or model updates without revealing individual
Trust and reputation mechanisms can reduce the influence of malicious clients in federated learning (FL), but strict upd
Differential privacy (DP) is a gold-standard definition of privacy designed to evaluate the privacy guarantee of databas
Autonomous cyber-defense agents trained using reinforcement learning (RL) are increasingly adopted for defending enterpr
Modern maritime navigation depends on mandatory wireless inputs, most notably GNSS and AIS, whose reception can be spoof