2 天前 - … background of deep learning model, such as autoencoders, adversarial autoencoders,
… have discussed evaluation for adversarial autoencoders for intrusion detection, using …

5 天前 - … Based on this analysis of adversarial observations, the attack’s adversarial budget
will be reduced until the observations it produces appear plausible. Attacks in this work use …

7 天前 - … Our investigation extends to deep learning models tailored for intrusion detection, …
intricate Resnet50 deep model. We systematically generate imperceptible adversarial inputs …

10 天前 - … power systems leading to overfitting and reduced detection accuracy… learning
based IDS for power systems by leveraging Conditional Tabular Generative Adversarial Networks …

10 天前 - … and cyber attack detection have grown in significance. Machine learning techniques
offer a … been bringing the capabilities of machine learning (ML) to use to make their security …

11 天前 - … intrusion detection systems (NIDS). By developing novel … been published as “Adversarial
machine learning for network intrusion detection systems: a comprehensive survey” in …

13 天前 - … the edge of the network. Many artificial intelligence (AI) applications such as smart
assistant, driverless cars, and smart city powered by machine learning demand low latency …

14 天前 - … of machine learning techniques in intrusion detection … purifying adversarial
examples in network intrusion detection… configurations maximizing adversarial robustness with …

14 天前 - … -art deep learning-based systems to identifying deepfake videos by developing a
model for deepfake detection… , referred to as deep adversarial models (for instance, generative …

14 天前 - … prepares datasets for training deep learning models, … than the facial hair detection
systems available. These results … It incorporates the use of Generative Adversarial Networks (…