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Real-time Cyber-Physical Security Solution Leveraging an Integrated Learning-Based Approach

Authors:

Xi ZhangAuthors Info & Claims

ACM Transactions on Sensor Networks, Volume 20, Issue 2

Article No.: 27, Pages 1 - 22

https://doi.org/10.1145/3582009

Published: 09 January 2024 Publication History

Abstract

Cyber-Physical Systems (CPS) has emerged as a paradigm that connects cyber and physical worlds, which provides unprecedented opportunities to realize intelligent applications such as smart home, smart cities, and smart manufacturing. However, CPS faces a great number of information security challenges (e.g., attacks) due to the integration of CPS as well as the human behaviors and interactions. Therefore, accurate and real-time attack detection and identification are essential to ensure information security and reliability of CPS. In this paper, we propose a novel integrated learning method that accurately detects an attack of a CPS system and then identifies the attack type in real time. Specifically, we consider a One-Class Support Vector Machine (OCSVM) model that only relies on the data from the normal state for training to achieve a real-time and effective detection of a CPS system state (i.e., normal or under-attack). If the system is detected to be under-attack, we then develop a Pairwise Self-supervised Long Short-Term Memory (PSLSTM) approach to identify the attack type, which aims to accurately distinguish the known attack types and discover unknown new attacks. Lastly, experimental results show the proposed method achieves promising performances compared with conventional and state-of-the-art learning-based benchmarks.

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Cited By

Fu LLiu YZhang YLi M(2024)Network Information Security Monitoring Under Artificial Intelligence EnvironmentInternational Journal of Information Security and Privacy10.4018/IJISP.34503818:1(1-25)Online publication date: 21-Jun-2024
https://dl.acm.org/doi/10.4018/IJISP.345038
Alsufyani ARana OPerera C(2024)Knowledge-based Cyber Physical Security at Smart Home: A ReviewACM Computing Surveys10.1145/3698768Online publication date: 3-Oct-2024
https://doi.org/10.1145/3698768
Gao HSu YWang FLi H(2024)Heterogeneous Fusion and Integrity Learning Network for RGB-D Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365647620:7(1-24)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3656476
Show More Cited By

Index Terms

Real-time Cyber-Physical Security Solution Leveraging an Integrated Learning-Based Approach
1. Security and privacy
  1. Intrusion/anomaly detection and malware mitigation
    1. Intrusion detection systems

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cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 20, Issue 2

March 2024

572 pages

EISSN:1550-4867

DOI:10.1145/3618080

Editor:
Wen Hu
University of New South Wales, Australia

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 09 January 2024

Online AM: 25 January 2023

Accepted: 04 November 2022

Revised: 21 September 2022

Received: 18 May 2022

Published in TOSN Volume 20, Issue 2

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National Science Foundation of China
Shanghai Sailing Program
National Science Foundation of Shanghai
Shanghai Chenguang Program

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Cited By

Fu LLiu YZhang YLi M(2024)Network Information Security Monitoring Under Artificial Intelligence EnvironmentInternational Journal of Information Security and Privacy10.4018/IJISP.34503818:1(1-25)Online publication date: 21-Jun-2024
https://dl.acm.org/doi/10.4018/IJISP.345038
Alsufyani ARana OPerera C(2024)Knowledge-based Cyber Physical Security at Smart Home: A ReviewACM Computing Surveys10.1145/3698768Online publication date: 3-Oct-2024
https://doi.org/10.1145/3698768
Gao HSu YWang FLi H(2024)Heterogeneous Fusion and Integrity Learning Network for RGB-D Salient Object DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/365647620:7(1-24)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3656476
Wang SYan YHan FTian YDing YYang PLi XOkoshi TKo JLiKamWa R(2024)MultiRider: Enabling Multi-Tag Concurrent OFDM Backscatter by Taming In-band InterferenceProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661862(292-303)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661862
Wang DXian XSong C(2024)Joint Learning of Failure Mode Recognition and Prognostics for Degradation ProcessesIEEE Transactions on Automation Science and Engineering10.1109/TASE.2023.323900421:2(1421-1433)Online publication date: Apr-2024
https://doi.org/10.1109/TASE.2023.3239004
Ji RKumar NPadha D(2024)CNN-GWO-voting & hybrid: ensemble learning inspired intrusion detection approaches for cyber-physical systemsProceedings of the Indian National Science Academy10.1007/s43538-024-00372-0Online publication date: 26-Nov-2024
https://doi.org/10.1007/s43538-024-00372-0
Xue MXu ZQiao SZheng JLi TWang YPeng D(2024)Driver intention prediction based on multi-dimensional cross-modality information interactionMultimedia Systems10.1007/s00530-024-01282-330:2Online publication date: 15-Mar-2024
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Wu ZGuo KWang LHu MRen S(undefined)A Collaborative Learning-based Urban Low-light Small-target Face Image Enhancement MethodACM Transactions on Sensor Networks10.1145/3616013
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