4 papers
Behavior-Aware and Generalizable Defense Against Black-Box Adversarial Attacks for ML-Based IDS
Sabrine Ennaji, Elhadj Benkhelifa, Luigi Vincenzo Mancini
Machine learning based intrusion detection systems are increasingly targeted by black box adversarial attacks, where attackers craft evasive inputs using indirect feedback such as…
Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS
Sabrine Ennaji, Elhadj Benkhelifa, Luigi V. Mancini
Adversarial attacks, wherein slight inputs are carefully crafted to mislead intelligent models, have attracted increasing attention. However, a critical gap persists between theore…
Toward Realistic Adversarial Attacks in IDS: A Novel Feasibility Metric for Transferability
Sabrine Ennaji, Elhadj Benkhelifa, Luigi Vincenzo Mancini
Transferability-based adversarial attacks exploit the ability of adversarial examples, crafted to deceive a specific source Intrusion Detection System (IDS) model, to also mislead…
MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark
William Corrias, Fabio De Gaspari, Dorjan Hitaj +1
Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwo…