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Telecommunication Systems
Published in: Telecommunication Systems 1/2022

27-06-2022

Implementing attack detection system using filter-based feature selection methods for fog-enabled IoT networks

Authors: Pooja Chaudhary, Brij Gupta, A. K. Singh

Published in: Telecommunication Systems | Issue 1/2022

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Abstract

Internet-of-Things (IoT) has become an enthralling attacking surface for attackers to explode multitude of cyber-attacks. Distributed Denial of Service (DDoS) attack has transpired as the most menacing attack in the IoT networks. In this article, we propose an attack detection system to identify anomalous activities in the fog-enabled IoT network. Initially, authors have investigated exhaustively on the performance of filter-based feature selection algorithms comprising ReliefF, Correlation Feature Selection (CFS), Information Gain (IG), and Minimum-Redundancy-Maximum-Relevancy (mRMR) and distinct categories classification algorithms upon the prepared dataset consisting of IoT network specific features. Performance of the tested classification algorithm is assessed using prominent evaluation measures. Moreover, response time of classifiers is calculated for centralized and fog-enabled IoT network infrastructure. The experimental outcomes unveil that, in terms of both accuracy and latency, J48 classifier outperforms all other tested classifier with mRMR feature selection algorithm.
previous article Correction to: EATMR: an energy-aware trust algorithm based the AODV protocol and multi-path routing approach in wireless sensor networks
next article Joint power control and user scheduling for backbone-assisted industrial wireless networks with successive interference cancellation

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Metadata
Title
Implementing attack detection system using filter-based feature selection methods for fog-enabled IoT networks
Authors
Pooja Chaudhary
Brij Gupta
A. K. Singh
Publication date
27-06-2022
Publisher
Springer US
Published in
Telecommunication Systems / Issue 1/2022
Print ISSN: 1018-4864
Electronic ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-022-00927-w

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