Improved Intrusion Detection System Based On Distributed Self-Adaptive Genetic Algorithm to Solve Support Vector Machine in Form of Multi Kernel Learning with Auto Encoder

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Faghihnia Elahe; Kamel Tabakh Farizani Seyed Reza; Kheirabadi Maryam

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Journal: Journal of Intelligent Procedures in Electrical Technology Year:2021 | Volume:12 | Issue:45 Page(s): 77-93

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Title

Improved Intrusion Detection System Based On Distributed Self-Adaptive Genetic Algorithm to Solve Support Vector Machine in Form of Multi Kernel Learning with Auto Encoder

Author(s)

Faghihnia Elahe | Kamel Tabakh Farizani Seyed Reza | Kheirabadi Maryam | Issue Writer Certificate

Keywords

Intrusion detection systems (IDS)Q1

support vector machine (SVM)Q2

big dataQ1

island genetic algorithm (IGA).self-adaptive genetic algorithm (SAGA)Q1

distributed self-adaptive genetic algorithm (DSAGA)Q1

Abstract

Intrusion into systems through network infrastructure and the Internet is one of the security challenges facing the world of information and communication technology and can lead to the destruction of systems and access to data and information. In this paper, a support vector machine model with weighted and parameters of SVM kernels are presented to detect the intrusion. Due to the high complexity of this problem, conventional optimization methods are not able to solve it. Therefore, we propose a Distributed Self Adaptive Genetic Algorithm (DSAGA). On the other hand, due to the high volume of data in such issues, Auto encoder has been used to reduce data. The proposed approach is a hybrid method based on Auto encoder, improved Support Vector Machine and Distributed Self Adaptive Genetic Algorithm (DSAGA) that it is evaluated by its execution on DARPA data set.

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APA: Copy

Faghihnia, Elahe, Kamel Tabakh Farizani, Seyed Reza, & Kheirabadi, Maryam. (2021). Improved Intrusion Detection System Based On Distributed Self-Adaptive Genetic Algorithm to Solve Support Vector Machine in Form of Multi Kernel Learning with Auto Encoder. JOURNAL OF INTELLIGENT PROCEDURES IN ELECTRICAL TECHNOLOGY, 12(45 ), 77-93. SID. https://sid.ir/paper/391748/en

Vancouver: Copy

Faghihnia Elahe, Kamel Tabakh Farizani Seyed Reza, Kheirabadi Maryam. Improved Intrusion Detection System Based On Distributed Self-Adaptive Genetic Algorithm to Solve Support Vector Machine in Form of Multi Kernel Learning with Auto Encoder. JOURNAL OF INTELLIGENT PROCEDURES IN ELECTRICAL TECHNOLOGY[Internet]. 2021;12(45 ):77-93. Available from: https://sid.ir/paper/391748/en

IEEE: Copy

Elahe Faghihnia, Seyed Reza Kamel Tabakh Farizani, and Maryam Kheirabadi, “Improved Intrusion Detection System Based On Distributed Self-Adaptive Genetic Algorithm to Solve Support Vector Machine in Form of Multi Kernel Learning with Auto Encoder,” JOURNAL OF INTELLIGENT PROCEDURES IN ELECTRICAL TECHNOLOGY, vol. 12, no. 45 , pp. 77–93, 2021, [Online]. Available: https://sid.ir/paper/391748/en

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