PJST 2 JUNE.pmd
نویسنده
چکیده
Research in the field of computer and network sciences demands for tools and methodology to test their security effectively. Intrusion Detection System is used to perform the same with a fact that an intruder’s behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. IDS have thousands of alerts per day; some are mistakenly triggered by begin events. This make it extremely difficult to correctly identify alerts related to attack. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons .Firstly the human immune system provides the human body with a high level of protection from invading pathogens in a robust, self organized and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. This research paper proposes a neural network approach to building network-based IDS, which is inspired by a artificial immune system to find the unseen or unknown attack. This paper will describe our efforts to determine if pattern recognition can serve to add to the adaptability of network intrusion detectors and improve the response time between intrusion and detection. We will look at several systems of pattern recognition to identify from them the most viable techniques and highlight the problems that exist in using pattern recognition and classification. Keyword: Intrusion detection system. Pattern Recognition
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PJST 2 JUNE.pmd
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