A Two-Level Hybrid Model for Anomalous Activity Detection in IoT Networks | IEEE Conference Publication | IEEE Xplore

A Two-Level Hybrid Model for Anomalous Activity Detection in IoT Networks


Abstract:

In this paper we propose a two-level hybrid anomalous activity detection model for intrusion detection in IoT networks. The level-1 model uses flow-based anomaly detectio...Show More

Abstract:

In this paper we propose a two-level hybrid anomalous activity detection model for intrusion detection in IoT networks. The level-1 model uses flow-based anomaly detection, which is capable of classifying the network traffic as normal or anomalous. The flow-based features are extracted from the CICIDS2017 and UNSW-15 datasets. If an anomaly activity is detected then the flow is forwarded to the level-2 model to find the category of the anomaly by deeply examining the contents of the packet. The level-2 model uses Recursive Feature Elimination (RFE) to select significant features and Synthetic Minority Over-Sampling Technique (SMOTE) for oversampling and Edited Nearest Neighbors (ENN) for cleaning the CICIDS2017 and UNSW-15 datasets. Our proposed model precision, recall and F score for level-1 were measured 100% for the CICIDS2017 dataset and 99% for the UNSW-15 dataset, while the level-2 model precision, recall, and F score were measured at 100 % for the CICIDS2017 dataset and 97 % for the UNSW-15 dataset. The predictor we introduce in this paper provides a solid framework for the development of malicious activity detection in IoT networks.
Date of Conference: 11-14 January 2019
Date Added to IEEE Xplore: 28 February 2019
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Conference Location: Las Vegas, NV, USA
Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, Canada
Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, Canada

Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, Canada
Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, Canada
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