An Overview of Attacks and Defences on Intelligent Connected Vehicles
July 17, 2019 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: An Overview of Attacks and Defences on Intelligent Connected Vehicles"
Evidence collected by the PWNC Scanner
Authors
Mahdi Dibaei, Xi Zheng, Kun Jiang, Sasa Maric, Robert Abbas, Shigang Liu, Yuexin Zhang, Yao Deng, Sheng Wen, Jun Zhang, Yang Xiang, Shui Yu
arXiv ID
1907.07455
Category
cs.CR: Cryptography & Security
Citations
46
Venue
arXiv.org
Last Checked
2 days ago
Abstract
Cyber security is one of the most significant challenges in connected vehicular systems and connected vehicles are prone to different cybersecurity attacks that endanger passengers' safety. Cyber security in intelligent connected vehicles is composed of in-vehicle security and security of inter-vehicle communications. Security of Electronic Control Units (ECUs) and the Control Area Network (CAN) bus are the most significant parts of in-vehicle security. Besides, with the development of 4G LTE and 5G remote communication technologies for vehicle-toeverything (V2X) communications, the security of inter-vehicle communications is another potential problem. After giving a short introduction to the architecture of next-generation vehicles including driverless and intelligent vehicles, this review paper identifies a few major security attacks on the intelligent connected vehicles. Based on these attacks, we provide a comprehensive survey of available defences against these attacks and classify them into four categories, i.e. cryptography, network security, software vulnerability detection, and malware detection. We also explore the future directions for preventing attacks on intelligent vehicle systems.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Cryptography & Security
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
The Limitations of Deep Learning in Adversarial Settings
R.I.P.
๐ป
Ghosted
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
R.I.P.
๐ป
Ghosted
Spectre Attacks: Exploiting Speculative Execution
R.I.P.
๐ป
Ghosted
How To Backdoor Federated Learning
R.I.P.
๐ป
Ghosted