Zeyong Sun1, Guo Ran2, Zilong Jin1,3,*
Journal on Internet of Things, Vol.4, No.2, pp. 99-111, 2022, DOI:10.32604/jiot.2022.037416
Abstract Intrusion detection is a hot field in the direction of network security. Classical intrusion detection systems are usually based on supervised machine learning models. These offline-trained models usually have better performance in the initial stages of system construction. However, due to the diversity and rapid development of intrusion techniques, the trained models are often difficult to detect new attacks. In addition, very little noisy data in the training process often has a considerable impact on the performance of the intrusion detection system. This paper proposes an intrusion detection system based on active incremental learning with the adaptive capability to solve… More >
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