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      Deep Learning Techniques for Cyber Security Intrusion Detection : A Detailed Analysis

      proceedings-article
      , , ,
      6th International Symposium for ICS & SCADA Cyber Security Research 2019 (ICS-CSR)
      Cyber Security Research
      10th-12th September 2019
      Deep Learning, intrusion detection, Cyber Security, machine learning
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            Abstract

            In this study, we present a detailed analysis of deep learning techniques for intrusion detection. Specifically, we analyze seven deep learning models, including, deep neural networks, recurrent neural networks, convolutional neural networks, restricted Boltzmann machine, deep belief networks, deep Boltzmann machines, and deep autoencoders. For each deep learning model, we study the performance of the model in binary classification and multiclass classification. We use the CSE-CIC-IDS 2018 dataset and TensorFlow system as the benchmark dataset and software library in intrusion detection experiments. In addition, we use the most important performance indicators, namely, accuracy, detection rate, and false alarm rate for evaluating the efficiency of several methods.

            Content

            Author and article information

            Contributors
            Conference
            September 2019
            September 2019
            : 126-136
            Affiliations
            [0001]Department of Computer Science

            Guelma University, Algeria
            [0002]School of Computer Science and Informatics

            De Montfort University, UK
            Article
            10.14236/ewic/icscsr19.16
            d01bfab2-d796-41d9-83a3-06d0cb5ffc48
            © Mohamed Amine Ferrag et al. Published by BCS Learning and Development Ltd. 6th International Symposium for ICS & SCADA Cyber Security Research 2019

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            6th International Symposium for ICS & SCADA Cyber Security Research 2019
            ICS-CSR
            6
            Athens, Greece
            10th-12th September 2019
            Electronic Workshops in Computing (eWiC)
            Cyber Security Research
            History
            Product

            1477-9358 BCS Learning & Development

            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/icscsr19.16
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Deep Learning,machine learning,Cyber Security,intrusion detection

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