Intelligent Network Intrusion Prevention Feature Collection and Classification Algorithms

• Published in: Algorithms Vol. 14; no. 8; p. 224
• Main Authors: Selva, Deepaa, Nagaraj, Balakrishnan, Pelusi, Danil, Arunkumar, Rajendran, Nair, Ajay
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2021
• Subjects: Datasets; Decision making; fuzzy concepts; Genetic algorithms; Intelligent networks; Internet; intrusion detection; Intrusion detection systems; Military applications; Neural networks; Quality of service architectures; selection techniques; Software agents; Swarm intelligence; Wireless networks
• ISSN: 1999-4893; 1999-4893
• DOI: 10.3390/a14080224

Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies offer protection in interactions in dispersed locations such as, e-commerce, mobile networking, telecommunications and management of network. Furthermore, this article proposed on intelligent feature selection methods and intrusion detection (ISTID) organization in webs based on neuron-genetic algorithms, intelligent software agents, genetic algorithms, particulate swarm intelligence and neural networks, rough-set. These techniques were useful to identify and prevent network intrusion to provide Internet safety and improve service value and accuracy, performance and efficiency. Furthermore, new algorithms of intelligent rules-based attributes collection algorithm for efficient function and rules-based improved vector support computer, were proposed in this article, along with a survey into the current smart techniques for intrusion detection systems.