An Adaptive Federated Learning Intrusion Detection System Based on Generative Adversarial Networks under the Internet of Things

Author:

Zhao Huiqi1ORCID,Liu Lu1ORCID,Fan Fang1ORCID,Zhang Huajie1ORCID,Ma Yaowen1ORCID

Affiliation:

1. College of Intelligent Equipment, Shandong University of Science and Technology, China

Publisher

ACM

Reference15 articles.

1. United We Stand: Collaborative Detection and Mitigation of Amplification DDoS Attacks at Scale

2. Lingjuan Lyu, Han Yu, and Qiang Yang. 2020. Threats to Federated Learning: A Survey. Retrieved November 10, 2023 from http://arxiv.org/abs/2003.02133

3. Deep learning approaches for anomaly-based intrusion detection systems: A survey, taxonomy, and open issues

4. Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative Adversarial Networks. Retrieved October 30, 2023 from http://arxiv.org/abs/1406.2661

5. On Defensive Neural Networks Against Inference Attack in Federated Learning

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