NANIND: A Novel Approach for Network Intrusion Detection

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AZEEZ, Nureni Ayofe
BABATOPE, Adeoluwa Bennard
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Transition from Observation to Knowledge to Intelligence
Information that is not properly secured has the tendency of being vulnerable to intrusions and threats. Security has become not just a feature of an information system, but the core and a necessity especially the systems that communicate and transmit data over the internet for they are more susceptible to intrusions and threats. This project aims at presenting a novel approach to intrusion detection. This thesis presents an Intrusion Detection System (IDS) using Genetic Algorithm (GA). GA was chosen because it has been proven to efficiently detect different types of intrusions. GA parameters and the evolution process are discussed in detail. The DARPA 1998 dataset was used to implement and measure the performance of the system. The result that was obtained showed that Class A IP addresses were more susceptible to intrusions and threats.
Intrusion, Genetic Algorithm, detection, Security, DARPA dataset
Azeez N.A and Babatope A (2016) “NANIND: “A Novel Approach for Network Intrusion Detection” 2016 International Conference on Transition from Observation to Information to Knowledge (TOKI-2016) at the University of Lagos, Thursday 25, August 2016- Friday 26, August 2016, pp 47-67.