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Implementation of "Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence," International Journal of Computer Applications 179(16):1-9, January 2018.

Home Page: http://www.ijcaonline.org/archives/volume179/number16/28880-2018916224

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swarm-intelligence intrusion-detection non-negative-matrix-factorization aco anomaly-detection algorithms software-engineering antcolony metaheuristics

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Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence

Implementation of "Intelligent Intrusion Detection in Computer Networks using Swarm Intelligence," International Journal of Computer Applications 179(16):1-9, January 2018.

Abstract

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.

Authors

  • Apoorv Saxena
  • Carsten Mueller

Online available at : doi>10.5120/ijca2018916224

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