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Quantum optimization for fast CAN bus intrusion detection

Published: 09 November 2022 Publication History

Abstract

Modern vehicles, nowadays, come loaded with hundreds of different sensors generating a huge amount of data. This data is shared and processed among different Electronic Control Units (ECUs) through an in-vehicle network, such as the CAN bus, to improve the driver’s experience and safety. However, the implementation of new features increases exposure to cyber-attacks. The CAN bus, which is designed to grant reliable communication, has many security weaknesses that might be exploited by an attacker. The need for highly accurate real-time intrusion detection systems (IDSs) for the automotive industry is limited to classical machine learning techniques, which are usually time-consuming and have hardware limitations. In this work, we analyze an optimized and efficient version of a network-based IDS for CAN bus attack detection based on Quantum Annealing. The models were tested on two different CAN bus datasets. The results show that the Quantum Annealing algorithm outperforms a classical classification algorithm in terms of time performance, which is important in the identification of attacks in the automotive sector, and achieves similar results for detection accuracy.

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Cited By

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  • (2024)Efficient Crypto Engine for Authenticated Encryption, Data Traceability, and Replay Attack Detection Over CAN Bus NetworkIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.331254511:1(1008-1025)Online publication date: Jan-2024
  • (2024)Hybrid quantum architecture for smart city securityJournal of Systems and Software10.1016/j.jss.2024.112161217:COnline publication date: 1-Nov-2024
  • (2024)Quantum Machine Learning in Intrusion Detection Systems: A Systematic Mapping StudyIntelligent Sustainable Systems10.1007/978-981-99-7886-1_9(99-113)Online publication date: 9-Apr-2024
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cover image ACM Conferences
QP4SE 2022: Proceedings of the 1st International Workshop on Quantum Programming for Software Engineering
November 2022
36 pages
ISBN:9781450394581
DOI:10.1145/3549036
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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Publication History

Published: 09 November 2022

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Author Tags

  1. cybersecurity
  2. in-vehicle security
  3. quantum annealing
  4. quantum computing

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Cited By

View all
  • (2024)Efficient Crypto Engine for Authenticated Encryption, Data Traceability, and Replay Attack Detection Over CAN Bus NetworkIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.331254511:1(1008-1025)Online publication date: Jan-2024
  • (2024)Hybrid quantum architecture for smart city securityJournal of Systems and Software10.1016/j.jss.2024.112161217:COnline publication date: 1-Nov-2024
  • (2024)Quantum Machine Learning in Intrusion Detection Systems: A Systematic Mapping StudyIntelligent Sustainable Systems10.1007/978-981-99-7886-1_9(99-113)Online publication date: 9-Apr-2024
  • (2024)Machine Learning for Automotive Security in Technology TransferInformation Systems and Technologies10.1007/978-3-031-45651-0_34(341-350)Online publication date: 15-Feb-2024
  • (2023)CANAttack: Assessing Vulnerabilities within Controller Area NetworkSensors10.3390/s2319822323:19(8223)Online publication date: 2-Oct-2023
  • (2023)Artificial Intelligence for Automotive Security: How to Support Developers in Automotive Solutions2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)10.1109/MetroXRAINE58569.2023.10405720(954-959)Online publication date: 25-Oct-2023
  • (2023)A Novel Hybrid Quantum-Classical Framework for an In-Vehicle Controller Area Network Intrusion DetectionIEEE Access10.1109/ACCESS.2023.330433111(96081-96092)Online publication date: 2023
  • (2023)Quantum Annealing for Real-World Machine Learning ApplicationsQuantum Computing10.1007/978-3-031-37966-6_9(157-180)Online publication date: 7-Aug-2023

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