Heterogeneous Time Variant Activity Pattern Based Artificial Network Immune System for Intrusion Detection

Vasanthi, S.; Chandrasekar, S.
May 2014
Australian Journal of Basic & Applied Sciences;May2014, Vol. 8 Issue 7, p1
Academic Journal
Real World applications become more sophisticated and require more adaptable solutions with higher security constraints. Providing such solution with higher security is a challenging task for the service providers where there is higher risk and frequency of different kind of network attacks which arises from various network users. Identifying service attackers is a difficult task and needs a more intensive analysis, because there are situation when people send packets heavily and that increases the overall time delay with an increased hop count due to travelling in longer path. The main objective of the proposed system is to accurately detect the intrusion with less false positive and negative errors. The propose system also maintain high detection rate. We propose a heterogeneous activity pattern based approach which uses number of metrics to compute the genuiness of the incoming packets. The immune system monitors the incoming packet and extracts the heterogeneous time variant features like payload, time to live, hop count, access history, time variant connection, transfer rate. Using the heterogeneous time variant features we compute the legitimate weight. The legitimate weight is used to identify whether the packets is malicious or legitimate. The proposed method increases the performance of the immune system and Intrusion process up to 90% with the help of NASA rule.


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