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A systematic survey of attack detection and prevention in Connected and Autonomous Vehicles
Vehicular Communications ( IF 5.8 ) Pub Date : 2022-08-10 , DOI: 10.1016/j.vehcom.2022.100515
Trupil Limbasiya , Ko Zheng Teng , Sudipta Chattopadhyay , Jianying Zhou

The number of Connected and Autonomous Vehicles (CAVs) is increasing rapidly in various smart transportation services and applications, considering many benefits to society, people, and the environment. Several research surveys for CAVs were conducted by primarily focusing on various security threats and vulnerabilities in the domain of CAVs to classify different types of attacks, impacts of attacks, attack features, cyber-risk, defense methodologies against attacks, and safety standards. However, the importance of attack detection and prevention approaches for CAVs has not been discussed extensively in the state-of-the-art surveys, and there is a clear gap in the existing literature on such methodologies to detect new and conventional threats and protect the CAV systems from unexpected hazards on the road. Some surveys have a limited discussion on Attacks Detection and Prevention Systems (ADPS), but such surveys provide only partial coverage of different types of ADPS for CAVs. Furthermore, there is a scope for discussing security, privacy, and efficiency challenges in ADPS that can give an overview of important security and performance attributes.

This survey paper, therefore, presents the significance of CAVs in the market, potential challenges in CAVs, key requirements of essential security and privacy properties, various capabilities of adversaries, possible attacks in CAVs, and performance evaluation parameters for ADPS. An extensive analysis is discussed of different ADPS categories for CAVs and state-of-the-art research works based on each ADPS category that gives the latest findings in this research domain. This survey also discusses crucial and open security research problems that are required to be focused on the secure deployment of CAVs in the market.



中文翻译:

联网和自动驾驶汽车中攻击检测和预防的系统调查

考虑到对社会、人类和环境的诸多好处,在各种智能交通服务和应用中,联网和自动驾驶汽车 (CAV) 的数量正在迅速增加。对 CAV 进行了多项研究调查,主要关注 CAV 领域中的各种安全威胁和漏洞,以对不同类型的攻击、攻击的影响、攻击特征、网络风险、针对攻击的防御方法和安全标准进行分类。然而,CAV 攻击检测和预防方法的重要性尚未在最先进的调查中得到广泛讨论,现有文献中关于检测新的和传统威胁并保护 CAV 的方法存在明显差距。 CAV 系统免受道路上意外危险的影响。一些调查对攻击检测和预防系统 (ADPS) 的讨论有限,但此类调查仅提供了 CAV 不同类型 ADPS 的部分覆盖范围。此外,还有讨论 ADPS 中的安全、隐私和效率挑战的空间,可以概述重要的安全和性能属性。

因此,本调查报告介绍了 CAV 在市场中的重要性、CAV 的潜在挑战、基本安全和隐私属性的关键要求、对手的各种能力、CAV 中可能的攻击以及 ADPS 的性能评估参数。对 CAV 的不同 ADPS 类别和基于每个 ADPS 类别的最新研究工作进行了广泛的分析,从而提供了该研究领域的最新发现。本调查还讨论了需要重点关注 CAV 在市场上的安全部署的关键和开放的安全研究问题。

更新日期:2022-08-10
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