Adaptive Intrusion Detection Systems: Class Incremental Learning for IoT Emerging Threats
Author:
Affiliation:
1. University of Napoli Federico II,Napoli,Italy
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386129.pdf?arnumber=10386129
Reference33 articles.
1. Internet of Things (IoT): A vision, architectural elements, and future directions
2. Internet of Things security: A survey
3. Cross-evaluation of deep learning-based network intrusion detection systems;Guida
4. Network anomaly detection methods in IoT environments via deep learning: A Fair comparison of performance and robustness
5. On the use of Machine Learning Approaches for the Early Classification in Network Intrusion Detection
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Toward Ever-Evolution Network Threats: A Hierarchical Federated Class-Incremental Learning Approach for Network Intrusion Detection in IIoT;IEEE Internet of Things Journal;2024-09-15
2. MEMENTO: A novel approach for class incremental learning of encrypted traffic;Computer Networks;2024-05
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