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cs.CR2026
McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware
Md Mahmuduzzaman Kamol, Jesus Lopez, Saeefa Rubaiyet Nowmi +5
Machine learning (ML) in real-world systems must contend with concept drift, adversarial actors, and a spectrum of potential features with varying costs and benefits. Malware natur…
cs.CR2026
Evaluating Generalization Mechanisms in Autonomous Cyber Attack Agents
OndÅej Lukáš, Jihoon Shin, Emilia Rivas +6
Autonomous offensive agents often fail to transfer beyond the networks on which they are trained. We isolate a minimal but fundamental shift -- unseen host/subnet IP reassignment i…
cs.CR2025
Adapting Under Fire: Multi-Agent Reinforcement Learning for Adversarial Drift in Network Security
Emilia Rivas, Sabrina Saika, Ahtesham Bakht +3
Evolving attacks are a critical challenge for the long-term success of Network Intrusion Detection Systems (NIDS). The rise of these changing patterns has exposed the limitations o…