The week's pick
Reseach Article
Enhancing the Efficiency of Detecting Intrusions using Improved PSOGMM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 18 |
| Year of Publication: 2019 |
| Authors: Anidua Bano, Pankaj Sharma |
10.5120/ijca2019919021
|
Anidua Bano, Pankaj Sharma . Enhancing the Efficiency of Detecting Intrusions using Improved PSOGMM. International Journal of Computer Applications. 178, 18 ( Jun 2019), 19-23. DOI=10.5120/ijca2019919021
Abstract
Network security is one of the most significant problems in computer network management and intrusion. In recent years, the intrusion has occurred as a major area of security for the network. Each section of the attacks is considered to be a particular problem and IDS are doing well when specialized algorithms are handled. Several surveys show that penetration in the network has been steadily increased and has led to private privacy theft. It is an important platform for recent attacks. A network intrusion is illegal activities in the computer network. It is, therefore, necessary to improve an operative intrusion system. In this paper, we use improved particle swarm optimization Gaussian mixture model (IPSOGMM) to detect infiltrative inspection. This paper shows compatibility between an integrated system using an IGKM algorithm and an interchange control system used by the IPSOGMM algorithm in the KDD-99 dataset. Finding that the test was discovered uses IPSOGMM algorithm is additionally correct when compared to IGKM algorithm.
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