A Synthetic Reverse Model Based on AIS and the Application
作者： Chang-You Zhang , Wen-Qing Li , Yuan-Da Cao , Zeng-Lu Fan
DOI: 10.1007/978-3-642-10238-7_20
关键词: Point (geometry) 、 Computer science 、 Position (vector) 、 Abscissa 、 Cartesian coordinate system 、 Artificial immune system 、 Ordinate 、 Set (abstract data type) 、 Genetic algorithm 、 Algorithm
摘要: Artificial Immune System (AIS) is a set of principles and algorithm following the properties nature immune system. In order to improve performance IDS, synthetic dimension reduction model proposed in this paper. First all, we define similarity distance between two vectors based on analogy reasoning. Then, introduce an optimization method meliorate normal-behavior-set abnormal-behavior-set AIS Genetic Algorithm (GA). And then, construct reverse taking both above mentioned behaviour set. When new behavior sample sniffered from network, distances each meliorated sets are calculated. Finally, treat these as ordinate abscissa, mapped multi-dimensional vector space into point two-dimensional coordinate plane. According position point, determine whether intrusion or not.
springer.com
sci-hub.st 参考文章(15)
Dong Seong Kim, Jong Sou Park, Network-based Intrusion Detection with Support vector machines international conference on information networking. pp. 747- 756 ,(2003) , 10.1007/978-3-540-45235-5_73
Mike Fugate, James R. Gattiker, Anomaly Detection Enhanced Classification in Computer Intrusion Detection Lecture Notes in Computer Science. pp. 186- 197 ,(2002) , 10.1007/3-540-45665-1_15
H. S. Seung, COGNITION: The Manifold Ways of Perception Science. ,vol. 290, pp. 2268- 2269 ,(2000) , 10.1126/SCIENCE.290.5500.2268
Jong Sou Park, Khaja Mohammad Shazzad, Dong Seong Kim, Toward Modeling Lightweight Intrusion Detection System Through Correlation-Based Hybrid Feature Selection Information Security and Cryptology. pp. 279- 289 ,(2005) , 10.1007/11599548_24
Zhang Changyou, Cao Yuanda, Yang Minghua, Yu Jiong, Zhu Dongfeng, Immune recognition method based on analogy reasoning in intrusion detection system Wuhan University Journal of Natural Sciences. ,vol. 11, pp. 1839- 1843 ,(2006) , 10.1007/BF02831888
Carol Taylor, Jim Alves-Foss, NATE: Network Analysis of Anomalous Traffic Events, a low-cost approach new security paradigms workshop. pp. 89- 96 ,(2001) , 10.1145/508171.508186
Shi-Jinn Horng, Pingzhi Fan, Yao-Ping Chou, Yen-Cheng Chang, Yi Pan, A feasible intrusion detector for recognizing IIS attacks based on neural networks Computers & Security. ,vol. 27, pp. 84- 100 ,(2008) , 10.1016/J.COSE.2008.04.004
Niels Kaj Jerne, The immune system. Scientific American. ,vol. 229, pp. 52- 60 ,(1973) , 10.1038/SCIENTIFICAMERICAN0773-52
Animesh Patcha, Jung-Min Park, None, Network anomaly detection with incomplete audit data Computer Networks. ,vol. 51, pp. 3935- 3955 ,(2007) , 10.1016/J.COMNET.2007.04.017
R.A. Kemmerer, G. Vigna, Intrusion detection: a brief history and overview IEEE Computer. ,vol. 35, pp. 27- 30 ,(2002) , 10.1109/MC.2002.1012428