Title :
Multi-objective functions in particle swarm optimization for intrusion detection
Author :
Cleetus, Nimmy ; Dhanya, K.A.
Author_Institution :
Dept. of Comput. Sci. & Eng., SCMS Sch. of Eng. & Technol., Ernakulam, India
Abstract :
The paper constitutes the study of particle swarm optimization in multi-objective functions. Swarm intelligence plays a vital role in intrusion detection. Intrusion detection system identifies the normal as well as abnormal behavior of a system. The weighted aggregation method is considered as multi-objective functions. We propose an intrusion detection mechanism based on particle swarm optimization which has a strong global search capability and used for the dimensionality optimization. Random forest is used as the classifier for modelling attacks and legitimate set. An accuracy of 91.71% at detection time of 0.22sec is obtained.
Keywords :
particle swarm optimisation; search problems; security of data; swarm intelligence; attacks modelling; dimensionality optimization; global search capability; intrusion detection; legitimate set; multiobjective functions; particle swarm optimization; swarm intelligence; weighted aggregation method; Accuracy; Birds; Feature extraction; Intrusion detection; Noise measurement; Optimization; Particle swarm optimization; Particle Swarm Optimization; fitness function; intrusion detection; multi-objective functions;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4799-3078-4
DOI :
10.1109/ICACCI.2014.6968613
