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Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems
Our experiments suggest that the state-of-the-art algorithms used in this study are sensitive to data contamination and reveal the importance of self-defense against data perturbation when developing novel models, especially for intrusion detection systems.
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