International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 179 - Number 16 |
Year of Publication: 2018 |
Authors: Apoorv Saxena, Carsten Mueller |
10.5120/ijca2018916224 |
Apoorv Saxena, Carsten Mueller . Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence. International Journal of Computer Applications. 179, 16 ( Jan 2018), 1-9. DOI=10.5120/ijca2018916224
Swarm Intelligence is inspired by the collective behaviour of many individuals. It is coordinated using decentralized control and self-organization. The individual simplicity and their complex group behaviours can outperform the vast majority of individual members when solving problems and making decisions. During recent years, the number of attacks on networks has dramatically increased and consequently, interest in network intrusion detection has increased among the researchers. In this research paper, a software architecture is modelled and implemented which uses Ant Colony Optimization (ACO), ACO is combined with Non-Negative Matrix Factorization method for classifying a computer network behaviour as a sequence of system calls.