Back Propagation Algorithm-Based Intelligent Model for Botnet Detection

被引:0
作者
Sunaidi, Nik Quosthoni [1 ]
Ahmed, Abdulghani Ali [1 ]
机构
[1] Univ Malaysia Pahang, Fac Comp Syst & Software Engn, Gambang 26300, Pahang, Malaysia
关键词
Back-Propagation; Neural Network; Machine Learning; Botnet;
D O I
10.1166/asl.2018.12940
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The ever-increasing growth of network computers and the internet of things makes botnet recognition become more difficult and it is making it all the more less difficult for intruders and attackers to propagate botnet infections. The unified propagation character of botnet floods warms through different botnet environment and clients the network security. To conquer the down sides in determining the botnet, we propose a back-propagation algorithm for botnet recognition. The focus of this study is a proposed back propagation algorithm in for training the sensor leveraging the machine learning techniques, which will keep an eye on attributes of the identified or recognized traffic flow. For every identified attribute recognized, it quickly identifies, which will include nine attributes used and identify it altogether. Every time the traffic is determined, its flow is tracked and weighed against the set of attributes within the feature set for the event of address within the network route.
引用
收藏
页码:7348 / 7354
页数:7
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