Abstract
Cloud computing is an important innovation in the current computing model. The critical problem of cloud computing faced at present is the security issue. In the current network environment, that relying on a single terminal to check the Trojan virus is considered increasingly unreliable. Based on the correspondence between the artificial immune system antibody and pathogen invasion intensity, this paper is to establish a real-time network risk evaluation model in cloud computing. This paper builds a hierarchical, quantitative measurement indicator system, and a unified evaluation information base and knowledge base. The paper also combines assets evaluation system and network integration evaluation system, considering from the application layer, the host layer, network layer may be factors that affect the network risks. The experimental results show that the new model improves the ability of intrusion detection and prevention than that of the traditional intrusion prevention systems.
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References
http://www.mysql.com/news-and-events/sun-to-acquire-mysql.html
Phurivit, S., Naruemon, W., Chalermpol, C.: Practical real-time intrusion detection using machine learning approaches. Computer Communications 34(18), 2227–2235 (2011)
Elshoush, H.T.: Alert correlation in collaborative intelligent intrusion detection systems-A survey. Applied Soft Computing 11(7), 4349–4365 (2011)
Amiri, F., Mahdi, M., Yousefi, R.: Mutual information-based feature selection for intrusion detection systems. Journal of Network and Computer Applications 34(4), 1184–1199 (2011)
Toubiana, V., Labiod, H., Reynaud, L.: A global security architecture for operated hybrid WLAN mesh networks. Computer Networks 54(2), 218–230 (2010)
Kuby, J.: Immunology. Fifith Edition by Richard A. Goldsby et al
Burnet, F.M.: The Clone Selection Theory of Acquired Immunity. Cambridge University Press, Cambridge (1959)
Hofmeyr, S.A., Forrest, S.: Architecture for an artificial immune system. Evolutionary Computation 8, 443–473 (2000)
Forrest, S., Perelson, A.S., Allen, L., Cherukuri, R.: Self-Nonself Discrimination in a Computer. In: Proceedings of IEEE Symposium on Research in Security and Privacy, Oakland (1994)
Atay, S., Masera, M.: Challenges for the security analysis of Next Generation Networks. Information Security Technical Report 16(1), 3–11 (2011)
Li, T.: An immunity based network security risk estimation. Science in China Ser. F Information Sciences 48, 557–578 (2005)
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Yang, J., Wang, C., Yu, L., Liu, C., Peng, L. (2012). Network Security Evaluation Model Based on Cloud Computing. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34041-3_68
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DOI: https://doi.org/10.1007/978-3-642-34041-3_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34040-6
Online ISBN: 978-3-642-34041-3
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