Abstract
Recently, Intrusion Detection Systems (IDS) have been deployed in the Internet for information security. Nevertheless, with the growing of Internet traffic, IDS becomes increasingly complicated and consumes much more energy. Existing studies concentrate on saving energy, but do not adapt to the change of network traffic. In this article, we propose a new method to adjust the frequency of IDS’s devices’ main processors automatically based on the prediction of the network traffic. It calculates optimal frequency scaling operation sequence via an internal sandbox model, so as to achieve energy saving purposes. Experiments show that our method can save 60 % power consumption generally.
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Acknowledgments
This work was supported by The National Science and Technology Support Program (Grant No. 2012BAH46B02); The Strategic Priority Research Program of the Chinese Academy of Sciences under (Grant No. XDA06030200); The National Natural Science Foundation (Grant No. 61402474).
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Lu, Q., Zhou, Z., Sha, H., Liu, Q., Sun, H. (2015). Self-Adaptive Frequency Scaling Architecture for Intrusion Detection System. In: Yueming, L., Xu, W., Xi, Z. (eds) Trustworthy Computing and Services. ISCTCS 2014. Communications in Computer and Information Science, vol 520. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47401-3_10
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DOI: https://doi.org/10.1007/978-3-662-47401-3_10
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