| An immunity-based technique to detect network intrusions |
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| 作者姓名： | 潘峰 丁云飞 汪为农 |
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| 作者单位： | Department of Computer Science and Engineering，Shanghai Jiaotong University，Shanghai 200030，China，Department of Automatic Control and Systems Engineering，University of Sheffield，Sheffield S10 2TN，UK，Department of Computer Science and Engineering，Shanghai Jiaotong University，Shanghai 200030，China |
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| 摘 要： | INTRODUCTION Research interest in immune system has in-creased over the past few years, and because of its special information processing capabilities, it has been applied to solve many problems (de Castro and Von Zuben, 1999; Hunt and Cooke, 1996). Among these research areas, network security is one of the hot spots and has been considered as analogous to im-munity in natural systems. Researchers at the Uni-versity of New Mexico did a lot of research in this area (Forrest et al., 199…
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| 关 键 词： | 人造免疫系统 网络入侵检测系统 网络安全 负选定 |
An immunity-based technique to detect network intrusions |
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| Pan Feng,Ding Yun-fei,Wang Wei-nong.An immunity-based technique to detect network intrusions[J].Journal of Zhejiang University Science,2005,6(5):371-377. |
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| Authors: | Pan Feng Ding Yun-fei Wang Wei-nong |
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| Institution: | 1. Department of Computer Science and Engineering, Shanghai Jiaotong University, 200030, Shanghai, China
2. Department of Automatic Control and Systems Engineering, University of Sheffield, S10 2TN, Sheffield, UK
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| Abstract: | This paper briefly reviews other people's works on negative selection algorithm and their shortcomings. With a view to the real problem to be solved, authors bring forward two assumptions, based on which a new immune algorithm, multi-level negative selection algorithm, is developed. In essence, compared with Forrest's negative selection algorithm, it enhances detector generation efficiency. This algorithm integrates clonal selection process into negative selection process for the first time. After careful analyses, this algorithm was applied to network intrusion detection and achieved good results. |
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| Keywords: | Artificial immune system Network intrusion detection Negative selection Clonal selection |
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