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Immune Recognition Method Based on Analogy Reasoning in Intrusion Detection System

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分类：TP305[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术]
作者机构：[1]School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China, [2]Computer Science and Technology Department, Shijiazhuang Railway Institute, Shijiazhuang 050043, Hebei, China, [3]College of Information University, Wulumuqi 830046, Science and Engineering, Xinjiang Xinjiang, China
相关基金：Supported by the National Natural Science Foundation of China （60563002） and Scientific Research Program of the Higher Education Institution of Xinjiang （XJEDU2004I03）
相关项目：非贡献分布式网格环境下性能预测和任务调度研究

关键词：免疫识别, 类似推理, 相似点, 遗传算法, 侵入检测系统, immune recognition, analogy reasoning, similarity, genetic algorithm, intrusion detection system

中文摘要：

在这篇论文，我们建议类比基于集中于克隆选择过程的工具的有免疫力的识别方法；借助于类比类似的否定选择过程。这个方法被使用在一跟随几个步骤的标志(侵入察觉系统) 。第一，起始的反常行为样品集合通过联合 AIS (人工的免疫系统) 被优化；基因算法。然后，反常概率算法就反常的二个方面而言被提起；规度。最后，一个侵入察觉系统模型基于上述算法被建立；模型。

英文摘要：

In this paper, we propose an analogy based immune recognition method that focuses on the implement of the clone selection process and the negative selection process by means of analogy similarity. This method is applied in an IDS （Intrusion Detection System） following several steps. Firstly, the initial abnormal behaviours sample set is optimized through the combining of the AIS （Artificial Immune System） and the genetic algorithm. Then, the abnormity probability algorithm is raised considering the two sides of abnormality and normality. Finally, an intrusion detection system model is established based on the above algorithms and models.

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