skip to main content
10.1145/3664476.3664512acmotherconferencesArticle/Chapter ViewAbstractPublication PagesaresConference Proceedingsconference-collections
research-article
Open access

Attack Analysis and Detection for the Combined Electric Vehicle Charging and Power Grid Domains

Published: 30 July 2024 Publication History

Abstract

With the steady rising Electric Vehicle (EV) adoption world-wide, a consideration of the Electric Vehicle (EV) charging-related load on power grids is becoming critically important. While strategies to manage this load (e.g., to avoid peaks) exist, they assume that Electric Vehicles (EVs) and charging infrastructure are trustworthy. If this assumption is, however, violated (e.g., by an adversary with control over Electric Vehicle (EV) charging systems), the threat of charging load-based attacks on grid stability arises. An adversary may, for example, try to cause overload situations, by means of a simultaneous increase in charging load coordinated over a large number of EVs. In this paper, we propose an Intrusion Detection System (IDS) that combines regression-based charging load prediction with novelty detection-based anomaly identification. The proposed system considers features from both the Electric Vehicle (EV) charging and power grid domains, which is enabled in this paper by a novel co-simulation concept. We evaluate our Intrusion Detection System (IDS) concept with simulated attacks in real Electric Vehicle (EV) charging data. The results show that the combination of support vector regression with isolation forest-based novelty detection generally provides the best results. Additionally, the evaluation shows that our Intrusion Detection System (IDS) concept, combining grid and charging features, is capable of detecting novel/stealthy attack strategies not covered by related work.

References

[1]
Sajjad Abedi, Ata Arvani, and Reza Jamalzadeh. 2015. Cyber security of plug-in electric vehicles in smart grids: application of intrusion detection methods. In Plug In Electric Vehicles in Smart Grids. Springer, 129–147.
[2]
Samrat Acharya, Yury Dvorkin, and Ramesh Karri. 2020. Public plug-in electric vehicles+ grid data: Is a new cyberattack vector viable?IEEE Transactions on Smart Grid (2020).
[3]
S Ahmed and Fouad M Dow. 2016. Electric vehicle technology as an exploit for cyber attacks on the next generation of electric power systems. In 2016 4th International Conference on Control Engineering & Information Technology (CEIT). IEEE, 1–5.
[4]
Abdullah Albarakati, Bassam Moussa, Mourad Debbabi, Amr Youssef, Basile L Agba, and Marthe Kassouf. 2018. Openstack-based evaluation framework for smart grid cyber security. In 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). IEEE, 1–6.
[5]
G Brooke Anderson and Michelle L Bell. 2012. Lights out: impact of the August 2003 power outage on mortality in New York, NY. Epidemiology (Cambridge, Mass.) 23, 2 (2012), 189.
[6]
Lennart Bader, Martin Serror, Olav Lamberts, Ömer Sen, Dennis van der Velde, Immanuel Hacker, Julian Filter, Elmar Padilla, and Martin Henze. 2023. Comprehensively Analyzing the Impact of Cyberattacks on Power Grids. (2023).
[7]
Emmanuel Balogun, Elizabeth Buechler, Siddharth Bhela, Simona Onori, and Ram Rajagopal. 2023. EV-EcoSim: A grid-aware co-simulation platform for the design and optimization of electric vehicle charging infrastructure. IEEE Transactions on Smart Grid (2023).
[8]
Defense Use Case. 2016. Analysis of the cyber attack on the Ukrainian power grid. Electricity Information Sharing and Analysis Center (E-ISAC) 388 (2016).
[9]
Stephen Checkoway, Damon McCoy, Brian Kantor, Danny Anderson, Hovav Shacham, Stefan Savage, Karl Koscher, Alexei Czeskis, Franziska Roesner, Tadayoshi Kohno, 2011. Comprehensive experimental analyses of automotive attack surfaces. In USENIX Security Symposium, Vol. 4. San Francisco, 2021.
[10]
Gong Chen, Yanfeng Qu, and Dong Jin. 2022. Cyber-Physical Simulation Testbed for MadIoT Attack Detection and Mitigation. In Proceedings of the 2022 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. 59–60.
[11]
Yu-Wei Chung, Mervin Mathew, Cole Rodgers, Bin Wang, Behnam Khaki, Chicheng Chu, and Rajit Gadh. 2020. The framework of invariant electric vehicle charging network for anomaly detection. In IEEE Transportation Electrification Conference & Expo.
[12]
David Coats, Harish Suryanarayana, Zhenyuan Wang, Alex Brissette, Yuzhi Zhang, VR Ramanan, Don Scoffield, Duncan Woodbury, Nick Haltmeyer, and Austin Benzinger. 2021. Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX). Technical Report. ABB, Inc.
[13]
Jesus Cumplido, Cristina Alcaraz, and Javier Lopez. 2022. Collaborative Anomaly Detection System for Charging Stations. In European Symposium on Research in Computer Security. Springer, 716–736.
[14]
Mathias Dalheimer. 2017. Chaos Computer Club hacks e-motor charging stations. https://www.ccc.de/en/updates/2017/e-motor
[15]
Satadru Dey and Munmun Khanra. 2020. Cybersecurity of Plug-In Electric Vehicles: Cyberattack Detection During Charging. IEEE Transactions on Industrial Electronics (2020).
[16]
Nan Duan, Nathan Yee, Benjamin Salazar, Jhi-Young Joo, Emma Stewart, and Ed Cortez. 2020. Cybersecurity analysis of distribution grid operation with distributed energy resources via co-simulation. In 2020 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 1–5.
[17]
ElaadNL. 2019. ElaadNL Open EV Charging Transactions. platform.elaad.io/download-data/
[18]
Hossam ElHussini, Chadi Assi, Bassam Moussa, Ribal Atallah, and Ali Ghrayeb. 2021. A tale of two entities: Contextualizing the security of electric vehicle charging stations on the power grid. ACM Transactions on Internet of Things 2, 2 (2021), 1–21.
[19]
Federal Highway Administration. 2023. National Electric Vehicle Infrastructure Standards and Requirements. Final rule. FHWA.
[20]
Federal Office for Information Security. 2023. FAQ on attack detection systems. https://www.bsi.bund.de/EN/Themen/KRITIS-und-regulierte-Unternehmen/Kritische-Infrastrukturen/KRITIS-FAQ/FAQ-Systeme-Angriffserkennung/faq-systeme-angriffserkennung_node.html
[21]
Simon Haverkamp and Martin Simons. 2022. Cybersecurity in the charging ecosystem – Status quo and stakeholder ambitions. Report. https://www.charin.global/media/pages/news/charin-task-force-cybersecurity/af8d69da69-1645626738/20220203-charging-ecosystem-stakeholder-landscape-rev_1.3.pdf
[22]
Bing Huang, Alvaro A Cardenas, and Ross Baldick. 2019. Not everything is dark and gloomy: Power grid protections against IoT demand attacks. In 28th USENIX Security Symposium (USENIX Security 19). 1115–1132.
[23]
IEC. 2018. Telecontrol equipment and systems – Part 5-104: Transmission protocols – Network access for IEC 60870-5-101 using standard transport profiles. IEC Standard 60870-5-104.
[24]
ISO/IEC. 2014. Road vehicles – Vehicle-to-Grid Communication Interface – Part 2: Network and application protocol requirements. ISO Standard 15118-2.
[25]
Jay Johnson, Timothy Berg, Benjamin Anderson, and Brian Wright. 2022. Review of Electric Vehicle Charger Cybersecurity Vulnerabilities, Potential Impacts, and Defenses. Energies 15, 11 (2022), 3931.
[26]
Sung-Kwan Joo, Jang-Chul Kim, and Chen-Ching Liu. 2007. Empirical analysis of the impact of 2003 blackout on security values of US utilities and electrical equipment manufacturing firms. IEEE Transactions on Power Systems 22, 3 (2007), 1012–1018.
[27]
Abdollah Kavousi-Fard, Tao Jin, Wencong Su, and Navid Parsa. 2020. An Effective Anomaly Detection Model for Securing Communications in Electric Vehicles. IEEE Transactions on Industry Applications (2020).
[28]
Dustin Kern and Christoph Krauß. 2021. Analysis of E-Mobility-based Threats to Power Grid Resilience. In Computer Science in Cars Symposium. 1–12.
[29]
Dustin Kern and Christoph Krauß. 2023. Detection of e-Mobility-based Attacks on the Power Grid. In 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 352–365.
[30]
Dustin Kern, Christoph Krauß, and Matthias Hollick. 2023. Detection of Anomalies in Electric Vehicle Charging Sessions. In Proceedings of the 39th Annual Computer Security Applications Conference. 298–309.
[31]
Nir Kshetri and Jeffrey Voas. 2017. Hacking power grids: A current problem. Computer 50, 12 (2017), 91–95.
[32]
Hua Lin, Yi Deng, Sandeep Shukla, James Thorp, and Lamine Mili. 2012. Cyber security impacts on all-PMU state estimator-a case study on co-simulation platform GECO. In 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm). IEEE, 587–592.
[33]
Xindong Liu, Mohammad Shahidehpour, Zuyi Li, Xuan Liu, Yijia Cao, and Zhaohong Bie. 2016. Microgrids for enhancing the power grid resilience in extreme conditions. IEEE Transactions on Smart Grid 8, 2 (2016), 589–597.
[34]
Xiaoxue Liu, Peidong Zhu, Yan Zhang, and Kan Chen. 2015. A collaborative intrusion detection mechanism against false data injection attack in advanced metering infrastructure. IEEE Transactions on Smart Grid 6, 5 (2015), 2435–2443.
[35]
Srinidhi Madabhushi and Rinku Dewri. 2021. Detection of Demand Manipulation Attacks on a Power Grid. In International Conference on Privacy, Security and Trust. IEEE.
[36]
Malaz Mallouhi, Youssif Al-Nashif, Don Cox, Tejaswini Chadaga, and Salim Hariri. 2011. A testbed for analyzing security of SCADA control systems (TASSCS). In ISGT 2011. IEEE, 1–7.
[37]
Samah Mansour, Géza Joós, Intissar Harrabi, and Martin Maier. 2013. Co-simulation of real-time decentralized vehicle/grid (RT-DVG) coordination scheme for e-mobility within nanogrids. In 2013 IEEE Electrical Power & Energy Conference. IEEE, 1–6.
[38]
Xiangyu Niu, Jiangnan Li, Jinyuan Sun, and Kevin Tomsovic. 2019. Dynamic detection of false data injection attack in smart grid using deep learning. In 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). IEEE, 1–6.
[39]
OCA. 2020. Open Charge Point Protocol 2.0.1. Open Standard. Open Charge Alliance, Netherlands. www.openchargealliance.org/protocols/ocpp-201/
[40]
Richard M Pratt and Thomas E Carroll. 2019. Vehicle charging infrastructure security. In 2019 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 1–5.
[41]
Panagiotis I Radoglou-Grammatikis and Panagiotis G Sarigiannidis. 2019. Securing the smart grid: A comprehensive compilation of intrusion detection and prevention systems. IEEE Access 7 (2019), 46595–46620.
[42]
Anuj Sanghvi and Tony Markel. 2021. Cybersecurity for electric vehicle fast-charging infrastructure. In 2021 IEEE Transportation Electrification Conference & Expo (ITEC). IEEE, 573–576.
[43]
Khaled Sarieddine, Mohammad Ali Sayed, Danial Jafarigiv, Ribal Atallah, Mourad Debbabi, and Chadi Assi. 2023. A Real-Time Cosimulation Testbed for Electric Vehicle Charging and Smart Grid Security. IEEE Security & Privacy (2023).
[44]
Saleh Soltan, Prateek Mittal, and H Vincent Poor. 2018. BlackIoT: IoT botnet of high wattage devices can disrupt the power grid. In 27th USENIX Security Symposium.
[45]
Florian Sommer, Jürgen Dürrwang, and Reiner Kriesten. 2019. Survey and classification of automotive security attacks. Information 10, 4 (2019), 148.
[46]
Remco A Verzijlbergh, Marinus OW Grond, Zofia Lukszo, Johannes G Slootweg, and Marija D Ilic. 2012. Network impacts and cost savings of controlled EV charging. IEEE transactions on Smart Grid 3, 3 (2012), 1203–1212.
[47]
Han Xiao, Yuan Huimei, Wei Chen, and Li Hongjun. 2014. A survey of influence of electrics vehicle charging on power grid. In 2014 9th IEEE Conference on Industrial Electronics and Applications. IEEE, 121–126.
[48]
Yue Yang and Jiarou Li. 2022. Electric Vehicle Charging Anomaly Detection Method Based on Multivariate Gaussian Distribution Model. In Proceedings of the Asia Conference on Electrical, Power and Computer Engineering. 1–6.
[49]
Maria Zhdanova, Julian Urbansky, Anne Hagemeier, Daniel Zelle, Isabelle Herrmann, and Dorian Höffner. 2022. Local Power Grids at Risk–An Experimental and Simulation-based Analysis of Attacks on Vehicle-To-Grid Communication. In Annual Computer Security Applications Conference. 42–55.
[50]
Ce Zhou, Qiben Yan, Zhiyuan Yu, Eshan Dixit, Ning Zhang, Huacheng Zeng, and Alireza Safdari Ghanhdari. 2023. ChargeX: Exploring State Switching Attack on Electric Vehicle Charging Systems. arXiv preprint arXiv:2305.08037 (2023).

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ARES '24: Proceedings of the 19th International Conference on Availability, Reliability and Security
July 2024
2032 pages
ISBN:9798400717185
DOI:10.1145/3664476
This work is licensed under a Creative Commons Attribution International 4.0 License.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 July 2024

Check for updates

Author Tags

  1. E-Mobility
  2. EV Charging
  3. False Data Injection
  4. Intrusion Detection System
  5. Manipulation of Demand
  6. Novelty Detection
  7. Regression
  8. Smart Grid

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

Conference

ARES 2024

Acceptance Rates

Overall Acceptance Rate 228 of 451 submissions, 51%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 347
    Total Downloads
  • Downloads (Last 12 months)347
  • Downloads (Last 6 weeks)104
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Login options

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media