activity
20242026
collaborators

23 papers

cs.CR2026

Feature-Space Bayesian Adversarial Learning Improved Malware Detector Robustness

Bao Gia Doan, Shuiqiao Yang, Paul Montague +6

We present a new algorithm to train a robust malware detector. Modern malware detectors rely on machine learning algorithms. Now, the adversarial objective is to devise alterations…

cs.CR2026

Original Sin of npm: A Study on Vulnerability Propagation in JavaScript Dependency Networks

Michael Robinson, Sajal Halder, Muhammad Ejaz Ahmed +3

Understanding vulnerability propagation is essential for assessing how vulnerabilities spread across components of a software package. This supports more accurate impact analysis a…

cs.LG2026

Parameter-efficient Quantum Multi-task Learning

Hevish Cowlessur, Chandra Thapa, Tansu Alpcan +1

Multi-task learning (MTL) improves generalization and data efficiency by jointly learning related tasks through shared representations. In the widely used hard-parameter-sharing se…

quant-ph2026

Quantum Spectral Authentication: Entity Authentication and Key Derivation from a Hidden Eigenstate of a Public Unitary Challenge

S. P. Kish, H. J. Vallury, J. Pieprzyk +2

We introduce Quantum Spectral Authentication (QSA), a symmetric-key entity-authentication and key-derivation protocol in which a remote endpoint proves it still holds a hidden plan…

cs.CR2026

DyMA-Fuzz: Dynamic Direct Memory Access Abstraction for Re-hosted Monolithic Firmware Fuzzing

Guy Farrelly, Michael Chesser, Seyit Camtepe +1

The rise of smart devices in critical domains--including automotive, medical, industrial--demands robust firmware testing. Fuzzing firmware in re-hosted environments is a promising…

cs.CR2026

TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation

Kristen Moore, Diksha Goel, Cody James Christopher +5

Realistic network traffic simulation is critical for evaluating intrusion detection systems, stress-testing network protocols, and constructing high-fidelity environments for cyber…