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Artificial immune system based intrusion detection

机译:基于人工免疫系统的入侵检测

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摘要

Due to the growing of internet applications, the needs of internet security are increasing. Intrusion detection system is the primary approaches used for saving systems from internal and external intruders. Several techniques have been applied to intrusion detection system such as artificial neural Network, genetic algorithms, artificial immune system. Most researchers suggested improving the intrusion detection performance and accuracy. In this paper, we used artificial immune system network based intrusion detection. In our framework we suggest using GureKddcup database set for intrusion detection and apply R-chunk algorithm of artificial immune system technique, it is used for anomaly detection .An optimized feature selection of rough set theory used for enhancing time consuming.
机译:由于互联网应用的增长,对互联网安全的需求也在增加。入侵检测系统是从内部和外部入侵者那里拯救系统的主要方法。几种技术已被应用于入侵检测系统,例如人工神经网络,遗传算法,人工免疫系统。大多数研究人员建议提高入侵检测性能和准确性。在本文中,我们使用了基于人工免疫系统网络的入侵检测。在我们的框架中,我们建议使用GureKddcup数据库集进行入侵检测,并应用人工免疫系统技术的R-chunk算法,将其用于异常检测。粗糙集理论的优化特征选择用于增加耗时。

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