Artificial immune system based intrusion detection

Eman Abd El Raoof Abas, H. Abdelkader, A. Keshk
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引用次数: 10

Abstract

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.
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基于人工免疫系统的入侵检测
随着互联网应用的不断增长,对网络安全的需求也在不断增加。入侵检测系统是保护系统免受内部和外部入侵的主要方法。人工神经网络、遗传算法、人工免疫系统等技术已被应用于入侵检测系统中。大多数研究人员建议提高入侵检测的性能和准确性。本文采用基于人工免疫系统网络的入侵检测方法。在我们的框架中,我们建议使用GureKddcup数据库集进行入侵检测,并采用人工免疫系统技术中的R-chunk算法进行异常检测,并采用粗糙集理论的优化特征选择来提高时间消耗。
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