Feature Selection of Network Intrusion Data using Genetic Algorithm and Particle Swarm Optimization
Journal Title: EMITTER International Journal of Engineering Technology - Year 2016, Vol 4, Issue 2
Abstract
This paper describes the advantages of using Evolutionary Algorithms (EA) for feature selection on network intrusion dataset. Most current Network Intrusion Detection Systems (NIDS) are unable to detect intrusions in real time because of high dimensional data produced during daily operation. Extracting knowledge from huge data such as intrusion data requires new approach. The more complex the datasets, the higher computation time and the harder they are to be interpreted and analyzed. This paper investigates the performance of feature selection algoritms in network intrusiona data. We used Genetic Algorithms (GA) and Particle Swarm Optimizations (PSO) as feature selection algorithms. When applied to network intrusion datasets, both GA and PSO have significantly reduces the number of features. Our experiments show that GA successfully reduces the number of attributes from 41 to 15 while PSO reduces the number of attributes from 41 to 9. Using k Nearest Neighbour (k-NN) as a classifier,the GA-reduced dataset which consists of 37% of original attributes, has accuracy improvement from 99.28% to 99.70% and its execution time is also 4.8 faster than the execution time of original dataset. Using the same classifier, PSO-reduced dataset which consists of 22% of original attributes, has the fastest execution time (7.2 times faster than the execution time of original datasets). However, its accuracy is slightly reduced 0.02% from 99.28% to 99.26%. Overall, both GA and PSO are good solution as feature selection techniques because theyhave shown very good performance in reducing the number of features significantly while still maintaining and sometimes improving the classification accuracy as well as reducing the computation time.
Authors and Affiliations
Iwan Syarif
Keywords
Related Articles
- EP ID EP269507
- DOI 10.24003/emitter.v4i2.149
- Views 133
- Downloads 0
Traffic Analysis of Quality of Service (QoS) for Video Conferencing between Main Campus and Sub Campus in Laboratory Scale
Recently, in the distance learning system, video conferencing becomes one of expected course material delivery systems for creating a virtual class such that lecturer and student which are separated at long distance can...
Performance of Channel Estimation Technique in MIMO-OFDM System Using mPSK Modulation
Multicarrier modulation technique as Orthogonal Frequency Division Multiplexing (OFDM) is able to vanishIntersymbol Interferences (ISI) caused by multipathchannel. Merging with multi- antenna transmission techniques such...
A Time-Series Phrase Correlation Computing System With Acoustic Signal Processing For Music Media Creation
This paper presents a system that analyzes the time-series impression change in the acoustic signal by a unit of music phrase. The aim is to support the music creation using a computer (computer music) by bringing out co...
Dimensionality Reduction Algorithms on High Dimensional Datasets
Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespeci...
Implementation of Energy Efficiency Based on Time Scheduling to Improve Network Lifetime in Wireless Body Area Network (WBAN)
ZigBee applications of IEEE 802.15.4 Wireless Sensor Network (WSN) with Low Rate Wireless Personal Area Network (LR-WPAN) can be integrated with e-health technology Wireless Body Area Network (WBAN). WBAN are small size...