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Hybrid GNN-LSTM defense with differential privacy and secure multi-party computation for edge-optimized neuromorphic autonomous systems. [PDF]
Sci RepRekik S, Mehmood S.
europepmc +1 more source
Intrusion Detection in the Internet of Things: A Comprehensive Review of Techniques, Architectures, Datasets, and Emerging Trends. [PDF]
Sensors (Basel)Komal A, Li S.
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Open-Set Adversarial Defense with Clean-Adversarial Mutual Learning [PDF]
International Journal of Computer Vision, 2022 Accepted by International Journal of Computer Vision (IJCV) 2022. Code will be available at https://github.com/rshaojimmy/ECCV2020-OSAD.
Rui Shao +2 more
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Adversarial Attacks and Defenses on Graphs
ACM SIGKDD Explorations Newsletter, 2021Deep neural networks (DNNs) have achieved significant performance in various tasks. However, recent studies have shown that DNNs can be easily fooled by small perturbation on the input, called adversarial attacks.
Wei Jin 0009 +6 more
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Sinkhorn Adversarial Attack and Defense
IEEE Transactions on Image Processing, 2022Adversarial attacks have been extensively investigated in the recent past. Quite interestingly, a majority of these attacks primarily work in the lp space. In this work, we propose a novel approach for generating adversarial samples using Wasserstein distance.
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Review of Artificial Intelligence Adversarial Attack and Defense Technologies
Applied Sciences (Switzerland), 2019 In recent years, artificial intelligence technologies have been widely used in computer vision, natural language processing, automatic driving, and other fields.
Shilin Qiu, Qihe Liu, Liu Qihe
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Adversarial Attacks and Defenses
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020Deep neural networks (DNN) have achieved unprecedented success in numerous machine learning tasks in various domains. However, the existence of adversarial examples leaves us a big hesitation when applying DNN models on safety-critical tasks such as autonomous vehicles and malware detection.
Han Xu 0002 +3 more
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DeepRobust: a Platform for Adversarial Attacks and Defenses
Proceedings of the AAAI Conference on Artificial Intelligence, 2021DeepRobust is a PyTorch platform for generating adversarial examples and building robust machine learning models for different data domains. Users can easily evaluate the attack performance against different defense methods with DeepRobust and get performance analyzing visualization.
Yaxin Li 0001 +3 more
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