Intelligent Network Intrusion Prevention Feature Collection and Classification Algorithms

被引:90
|
作者
Selva, Deepaa [1 ]
Nagaraj, Balakrishnan [2 ]
Pelusi, Danil [3 ]
Arunkumar, Rajendran [2 ]
Nair, Ajay [2 ]
机构
[1] Karpagam Univ, Dept Elect & Commun Engn, Coimbatore 641021, Tamil Nadu, India
[2] Rathinam Grp Inst, Rathinam Tech Campus, Coimbatore 641021, Tamil Nadu, India
[3] Univ Teramo, Fac Commun Sci, I-64100 Teramo, Italy
关键词
selection techniques; intrusion detection; neural networks; fuzzy concepts; PHISHING DETECTION;
D O I
10.3390/a14080224
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:13
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