Abstract
Traditional intrusion detection system is confronted with the pressure of processing massive network traffic data which increases sharply. Besides, its feature of static detection causes the weak adaptability for the network environment. To overcome the former problems, an architecture for network intrusion detection based on cloud computing and artificial immune principle is proposed. It consists of local intrusion detection sub-system and cloud computing platform which provides the services of intrusion detection. The local intrusion detection sub-system captures and simply preprocesses the network traffics. The cloud computing platform deals with the true transactions of intrusion detection. It interacts with the local intrusion detection sub-system through standard service interface and responds the intrusion detection requests of the local intrusion detection sub-system. Furthermore, it simulates the good features of artificial immune principle and adopts self-learning mechanism to evolve intrusion detection elements to make the proposed architecture adaptive for the real network environment.
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© 2012 Springer-Verlag Berlin Heidelberg
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Liu, C., Xie, C., Zhang, Y., Li, Q., Peng, L. (2012). An Architecture for Cloud Computing and Human Immunity Based Network Intrusion Detection. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_39
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DOI: https://doi.org/10.1007/978-3-642-33478-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33477-1
Online ISBN: 978-3-642-33478-8
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