Extraction of rules for intrusion detection in computer networks using a genetic algorithm

The IJNCPS's Authors that presented the article:

Keywords: Clustering, K-means, Fuzzy Logic, Genetic Algorithm


Influencing the collection of illegal actions that
compromise the integrity or access to a source. Intrusion
detection systems play an important role in detecting
infiltration and malformation in computer networks.
Intrusion detection systems can greatly control network
penetration. By this description, one of the tasks of
intrusion detection systems, detection of intrusion that
can be carried out by internal and external factors.
Detecting and preventing infiltration today is considered
as one of the main mechanisms in ensuring the security
of networks and computer systems and are generally
used alongside the firewalls and complementary
security. In this study, we introduced an intrusion
detection system using a multi-objective optimization
algorithm and genetic algorithm. Then the proposed
algorithm was implemented with MATLAB
programming language. To evaluate this system,
standard data was used, and it was shown that the use of
a multi-objective genetic algorithm increases the
accuracy of the proposed model; the proposed algorithm
has an accuracy of 98 percent.


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