NANIND: A Novel Approach for Network Intrusion Detection
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Date
2016-08-25
Authors
AZEEZ, Nureni Ayofe
BABATOPE, Adeoluwa Bennard
Journal Title
Journal ISSN
Volume Title
Publisher
Transition from Observation to Knowledge to Intelligence
Abstract
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.
Description
Keywords
Intrusion, Genetic Algorithm, detection, Security, DARPA dataset
Citation
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.