Dec 6, 2023 · In this paper, we propose a novel IDS architecture that can enhance the robustness of IDS against adversarial attacks by combining conventional machine ...
In this paper, we propose a novel IDS architecture that can enhance the robustness of IDS against adversarial attacks by combining conventional machine learning ...
Jul 26, 2024 · In this paper, we propose a novel IDS architecture that can enhance the robustness of IDS against adversarial attacks by combining conventional machine ...
Apr 12, 2024 · In this paper, we propose a novel IDS architecture that can enhance the robustness of IDS against adversarial attacks by combining conventional ...
A Simple Framework to Enhance the Adversarial Robustness of Deep Learning-based Intrusion Detection System · Xinwei Yuan, Shu Han, +3 authors. Fan Zhang ...
Apr 27, 2024 · The method proposed in [6] uses DL based Intrusion Detection Systems (DL-IDS), adversarial example (AE) detector and ML-Based IDS. The AE ...
In this paper, we propose a novel IDS architecture that can enhance the robustness of IDS against adversarial attacks by combining conventional machine learning ...
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Sep 12, 2024 · Nowadays, Deep Neural Networks (DNNs) report state-of-the-art results in many machine learning areas, including intrusion detection.
This paper developed an adversarial robust and explainable network intrusion detection system based on deep learning by applying adversarial training and ...
We also note that increasing strength of the adversarial examples defense used for the training helps to improve the robustness of the detector to some extent, ...