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Automatic Control and Computer Sciences

Erschienen in:

01.03.2021

Design of Anomaly-Based Intrusion Detection System Using Fog Computing for IoT Network

verfasst von: Prabhat Kumar, Govind P. Gupta, Rakesh Tripathi

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 2/2021

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Abstract

With increase in the demand for Internet of Things (IoT)-based services, the capability to detect anomalies such as malicious control, spying and other threats within IoT-based network has become a major issue. Traditional Intrusion Detection Systems (IDSs) cannot be used in typical IoT-based network due to various constraints in terms of battery life, memory capacity and computational capability. In order to address these issues, various IDSs have been proposed in literature. However, most of the IDSs face problem of high false alarm rate and low accuracy in anomaly detection process. In this paper, we have proposed a anomaly-based intrusion detection system by decentralizing the existing cloud based security architecture to local fog nodes. In order to evaluate the effectiveness of the proposed model various machine learning algorithms such as Random Forest, K-Nearest Neighbor and Decision Tree are used. Performance of our proposed model is tested using actual IoT-based dataset. The evaluation of the underlying approach outperforms in high detection accuracy and low false alarm rate using Random Forest algorithm.

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Titel: Design of Anomaly-Based Intrusion Detection System Using Fog Computing for IoT Network
verfasst von: Prabhat Kumar
Govind P. Gupta
Rakesh Tripathi
Publikationsdatum: 01.03.2021
Verlag: Pleiades Publishing
Erschienen in: Automatic Control and Computer Sciences / Ausgabe 2/2021
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411621020085

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