Effective Intrusion Detection Systems using Genetic Algorithm
Abstract
firewalls, cryptography techniques, have not proved themselves to
completely defend networks and systems from newly generated
malwares and attacks. Intrusion Detection Systems (IDS) are
useful to find the correct solution to solve the current problems and became an important part of any security network
infrastructure to detect these threats without generating any
problem to network. The basic purpose of IDS is to detect attacks
and their nature that may harm the computer system. Several
different approaches for intrusion detection are available as per
the literature. These approaches are broadly defined by three
ways: i) Signature based approach ii) Anomaly based approach
and iii) Hybrid approach that combines signature and anomaly
detection approaches. The proposed system works for signature
based concept using genetic algorithm as features selection and
detection .The system is tested on KDDCup99 and NSL-KDD
dataset using Weka3.6 classifiers and implemented classifier.
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