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Title |
Hybrid Approach for Optimised Intrusion Detection System |
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Author |
Mr.M.Mangaleswaran |
| Citation |
Vol. 25 No. 2 pp. 129-134 |
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Abstract |
Intrusion detection is an important way to ensure the protection of computers and networks. In this paper, a new intrusion detection system is proposed based on Hidden Conditional Random Fields. In order to improve the performance of HCRFs, we bring forward the Two-stage Feature Selection method, which contains Manual Feature Selection method and Backward Feature Elimination Wrapper method. The BFEW is an aspect selection method which is introduced based on wrapper approach. Experimental results on KDD99 dataset show that the proposed IDS not only have a great advantage in detection efficiency but also have a higher accuracy when compared with other well-known methods. With the ever increasing number and diverse type of attacks, including novel and previously invisible attacks, the success of an Intrusion Detection System is very essential. Hence there is high demand to reduce the threat level in networks to ensure the information and services accessible by them to be extra secure. In this paper we developed a practical test suite for getting better the competence and precision of an intrusion detection system use the layered CRFs. We set up altered types of checks at several levels in each layer .Our framework examine various attribute at every layer in order to effectively classify any infringe of security. Once the attack is detected, it is intimated through mobile phone to the system administrator for preservation the server system. We established experimentally that the layered CRFs can thus be more professional in detecting intrusions when compared with the other previously known techniques. |
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Keywords |
Intrusion detection system; Hidden conditional Random Fields; Conditional random fields; Anomalous Activity; Layer-based Intrusion Detection System. . |
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