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Title |
Investigating Identification Techniques of Attacks in Intrusion Detection Systems Using Data Mining Algorithms |
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Author |
Seyed Amir Agah |
| Citation |
Vol. 17 No. 5 pp. 174-181 |
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Abstract |
According to extraordinary growth of network-based services, intrusion detection has been introduced as an important and efficient issue in the direction of network’s security promotion. In order for coping with the infiltrators of networks and computerized systems, different methods have been codified which are called intrusion detection method the aim of which is that illegal usage and abuse and damaging the systems and computerized networks is recognized by both internal users and external attackers. Generally, intrusion detection methods are divided in to two main categories of abuse detection and abnormal behavior detection. In abuse detection method, known intrusion patterns are used for recognizing the intrusions but in abnormal behavior detection methods, normal behavior of the users has the main criterion. As a result, any inconsistent behavior with that is considered as an effort for permeating the system. In this paper, intrusion detection systems and their performance are considered and finally we will become familiar with intrusion detection methods including data mining algorithms. |
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Keywords |
Intrusion detection, computerized networks, security, data mining algorithms |
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