Intrusion Detection Based on Swarm Intelligence using mobile agent

Due to the increase in access of malicious data over the internet resources, intrusions Detection Systems (IDSs) have become the necessary component of the computer and information security framework. Although the field of IDSs is still developing, they are not able to detect all types of intrusions. New intelligent Intrusion Detection Systems (IDSs) which are based on sophisticated algorithms rather than current signature-base detections are in demand. This work discuss about the ways of implementing a swarm intelligence approach to data clustering to detect intrusions. Mobile agent technology is used to initially collecting data properties. These data are evaluated by the combining of the artificial Immune recognition system and the artificial fuzzy ants clustering systems. Our approach allows us to recognize not only known attacks but also to detect suspicious activity that may be the result on knowledge Discovery and Data Mining (KDDCup 1999) dataset compared to a standard learning schema that use the full dataset.