research-article

Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems

Authors:

Subhash Lakshminarayana,

David K. Y. YauAuthors Info & Claims

ACM Transactions on Cyber-Physical Systems, Volume 2, Issue 4

Article No.: 28, Pages 1 - 29

https://doi.org/10.1145/3226030

Published: 21 August 2018 Publication History

Abstract

Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the air gaps and aim at causing safety incidents and service disruptions. In this article, we study False Data Injection (FDI) attacks against railway Traction Power Systems (TPSes). Specifically, we analyze two types of FDI attacks on the train-borne voltage, current, and position sensor measurements—which we call efficiency attack and safety attack—that (i) maximize the system’s total power consumption and (ii) mislead trains’ local voltages to exceed given safety-critical thresholds, respectively. To counteract, we develop a Global Attack Detection (GAD) system that serializes a bad data detector and a novel secondary attack detector designed based on unique TPS characteristics. With intact position data of trains, our detection system can effectively detect FDI attacks on trains’ voltage and current measurements even if the attacker has full and accurate knowledge of the TPS, attack detection, and real-time system state. In particular, the GAD system features an adaptive mechanism that ensures low false-positive and negative rates in detecting the attacks under noisy system measurements. Extensive simulations driven by realistic running profiles of trains verify that a TPS setup is vulnerable to FDI attacks, but these attacks can be detected effectively by the proposed GAD while ensuring a low false-positive rate.

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Cited By

Chakrabarty SSikdar B(2023)Detection of Cyber Attacks on Railway Autotransformer Traction Power SystemsIEEE Transactions on Industry Applications10.1109/TIA.2023.330749659:6(7188-7200)Online publication date: Nov-2023
https://doi.org/10.1109/TIA.2023.3307496
Abdellaoui SDumitrescu EEscudero CZamaï E(2023)Cyber Threat Assessment in Monitoring Turnout Railway Systems2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)10.1109/ETFA54631.2023.10275401(1-8)Online publication date: 12-Sep-2023
https://doi.org/10.1109/ETFA54631.2023.10275401
Wang ZLiu X(2022)Cyber security of railway cyber-physical system (CPS) – A risk management methodologyCommunications in Transportation Research10.1016/j.commtr.2022.1000782(100078)Online publication date: Dec-2022
https://doi.org/10.1016/j.commtr.2022.100078
Show More Cited By

Index Terms

Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems
1. Networks
  1. Network types
    1. Cyber-physical networks
2. Security and privacy
  1. Intrusion/anomaly detection and malware mitigation
    1. Intrusion detection systems

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Published In

cover image ACM Transactions on Cyber-Physical Systems

ACM Transactions on Cyber-Physical Systems Volume 2, Issue 4

Special Issue on Medical CPS Papers

October 2018

313 pages

ISSN:2378-962X

EISSN:2378-9638

DOI:10.1145/3236466

Editor:
Tei-Wei Kuo
National Taiwan University, and Academia Sinica, Taiwan

Issue’s Table of Contents

Copyright © 2018 ACM.

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 ACM 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: 21 August 2018

Accepted: 01 September 2017

Revised: 01 May 2017

Received: 01 October 2016

Published in TCPS Volume 2, Issue 4

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National Cybersecurity R8D Directorate
National Research Foundation (NRF)
NSFC
Prime Minister's Office, Singapore
Start-up Grant at NTU
National Cybersecurity R8D Programme

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Cited By

Chakrabarty SSikdar B(2023)Detection of Cyber Attacks on Railway Autotransformer Traction Power SystemsIEEE Transactions on Industry Applications10.1109/TIA.2023.330749659:6(7188-7200)Online publication date: Nov-2023
https://doi.org/10.1109/TIA.2023.3307496
Abdellaoui SDumitrescu EEscudero CZamaï E(2023)Cyber Threat Assessment in Monitoring Turnout Railway Systems2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)10.1109/ETFA54631.2023.10275401(1-8)Online publication date: 12-Sep-2023
https://doi.org/10.1109/ETFA54631.2023.10275401
Wang ZLiu X(2022)Cyber security of railway cyber-physical system (CPS) – A risk management methodologyCommunications in Transportation Research10.1016/j.commtr.2022.1000782(100078)Online publication date: Dec-2022
https://doi.org/10.1016/j.commtr.2022.100078
Chakrabarty SSikdar B(2021)Detection of Cyber Attacks on Railway Autotransformer Traction Power Systems2021 IEEE 2nd International Conference on Smart Technologies for Power, Energy and Control (STPEC)10.1109/STPEC52385.2021.9718653(1-6)Online publication date: 19-Dec-2021
https://doi.org/10.1109/STPEC52385.2021.9718653
Ahmadi-Assalemi GAl-Khateeb HEpiphaniou GMaple C(2020)Cyber Resilience and Incident Response in Smart Cities: A Systematic Literature ReviewSmart Cities10.3390/smartcities30300463:3(894-927)Online publication date: 13-Aug-2020
https://doi.org/10.3390/smartcities3030046
Zhang ZDeng RYau DCheng PChen J(2020)On Hiddenness of Moving Target Defense against False Data Injection Attacks on Power GridACM Transactions on Cyber-Physical Systems10.1145/33727514:3(1-29)Online publication date: 12-Mar-2020
https://dl.acm.org/doi/10.1145/3372751

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