Sep 30, 2023 · This paper identifies and formalizes threats to the robustness of IDSs against adversarial evasion attacks.
However, these algorithms are vulnerable to meta-attacks, also known as adversarial evasion attacks, which are attacks that improve already existing attacks, ...
Intrinsic Weaknesses of IDSs to Malicious Adversarial Attacks and Their Mitigation ... Threats to adversarial training for idss and mitigation. In ...
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Hassan Chaitou's 3 research works with 1 citations, including: Intrinsic Weaknesses of IDSs to Malicious Adversarial Attacks and Their Mitigation.
Hassan Chaitou, Thomas Robert, Jean Leneutre, Laurent Pautet: Intrinsic Weaknesses of IDSs to Malicious Adversarial Attacks and Their Mitigation.
Deep learning-based IDS, in particular, are vulnerable to adversarial attacks based on Genera- tive Adversarial Networks (GAN). First, this paper identifies the ...
Oct 22, 2024 · Contrary to white-box attacks, GAN-based black-box attacks are considered weak, as attackers have no knowledge or only have superficial ...
This study explores the vulnerabilities of machine learning-based intrusion detection systems (IDSs) within in-vehicle networks (IVNs) to adversarial attacks.
Missing: Weaknesses | Show results with:Weaknesses
Oct 4, 2024 · However, DL-NIDS are susceptible to adversarial attacks that adversaries can exploit to compromise their performance, limiting their reliability ...
Missing: IDSs | Show results with:IDSs
This research addresses the sophisticated adversarial manipulations posed by attackers, aiming to undermine machine learning-based botnet detection systems.