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CNN-based anomaly detection for packet payloads of industrial control system

Published: 01 January 2021 Publication History
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  • Abstract

    Industrial control systems (ICSs) are more vulnerable to cyber threats owing to their network connectivity. The intrusion detection system(IDS) has been deployed to detect sophisticated cyber-attack but the existing IDS uses the packet header information for traffic flow detection. IDS is inefficient to detect packet deformation; therefore, we propose the adoption of packet payload in IDS to respond to a variety of attacks and high performance. Our proposed model detects packet modification and traffic flowby inspecting each packet and sequence of packets. For evaluation, cross verification is conducted to increase the reliability of the statistics.

    Cited By

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    • (2024)Semi-supervised attack detection in industrial control systems with deviation networks and feature selectionThe Journal of Supercomputing10.1007/s11227-024-06018-880:10(14600-14621)Online publication date: 1-Jul-2024
    • (2023)P3 AD: Privacy-Preserved Payload Anomaly Detection for Industrial Internet of ThingsIEEE Transactions on Network and Service Management10.1109/TNSM.2023.327386020:4(5103-5114)Online publication date: 1-Dec-2023
    • (2022)Intrusion Detection Model for Industrial Internet of Things Based on Improved AutoencoderComputational Intelligence and Neuroscience10.1155/2022/14062142022Online publication date: 1-Jan-2022

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    1. CNN-based anomaly detection for packet payloads of industrial control system
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            Published In

            cover image International Journal of Sensor Networks
            International Journal of Sensor Networks  Volume 36, Issue 1
            2021
            58 pages
            ISSN:1748-1279
            EISSN:1748-1287
            DOI:10.1504/ijsnet.2021.36.issue-1
            Issue’s Table of Contents
            This is an Open Access Article distributed under the CC BY license.

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            Inderscience Publishers

            Geneva 15, Switzerland

            Publication History

            Published: 01 January 2021

            Author Tags

            1. network security
            2. intrusion detection
            3. anomaly detection
            4. convolutional neural network
            5. industrial control system
            6. N-gram method
            7. single packet detection
            8. sequence detection

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            Cited By

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            • (2024)Semi-supervised attack detection in industrial control systems with deviation networks and feature selectionThe Journal of Supercomputing10.1007/s11227-024-06018-880:10(14600-14621)Online publication date: 1-Jul-2024
            • (2023)P3 AD: Privacy-Preserved Payload Anomaly Detection for Industrial Internet of ThingsIEEE Transactions on Network and Service Management10.1109/TNSM.2023.327386020:4(5103-5114)Online publication date: 1-Dec-2023
            • (2022)Intrusion Detection Model for Industrial Internet of Things Based on Improved AutoencoderComputational Intelligence and Neuroscience10.1155/2022/14062142022Online publication date: 1-Jan-2022

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