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LIAS: A Lightweight Incentive Authentication Scheme for Forensic Services in IoV

机译:LIAS:一种面向车联网取证服务的轻量级激励认证方案

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摘要

Internet of Vehicles (IoV) has become an indispensable data sensing and processing platform in Internet of Things (IoT) for intelligent transportation. The mounted cameras on the vehicles along with the fixed roadside cameras are utilized to provide pictorial services for IoV users and law enforcement agencies. For such forensic services, ensuring the security and privacy of vehicles while guaranteeing the efficiency of data transmission among vehicles is important. In this paper, we propose a lightweight incentive authentication scheme (LIAS) for forensic services in IoV. LIAS is developed on a three-tier architecture containing cloud layer, fog layer, and user layer. LIAS uses pairing-free certificateless signcryption, pseudonym update mechanism, and incentive mechanism to realize a secure anonymous authentication efficiently. We conduct correctness and security analysis, as well as performance analysis and evaluation to validate the high security and efficiency of LIAS. Experimental results reveal that, the communication and computation overheads as well as the message delay and packet loss of LIAS are much lower than those of state-of-the-art techniques. Note to Practitioners—This paper is motivated by the security and privacy issues of forensic services in IoV for intelligent transportation. Our goal is to improve the security and privacy of vehicles while guaranteeing the lightweight and incentive of data transmission among the vehicles. Fog-assisted IoV is introduced to fully utilize the capacities of near-user edge devices as well as the connections between fog nodes and devices. However, it still faces the difficulties in ensuring vehicles’ security and privacy. Moreover, vehicles’ information dissemination could be easily monitored because of the unavoidable defect of wireless communication. Thereby, it is essential to guarantee the security and privacy of vehicles while enhancing the efficiency of vehicles’ data transmission during the forensic service. To this end, this paper proposes a lightweight conditional anonymous authentication scheme for forensic services in IoV, which is developed based on the pairing-free technique to achieve secure anonymous authentication with high efficiency. This paper also designs a user tracing mechanism, incentive mechanism, and pseudonym update mechanism to realize safe and effective forensic service in IoV.
机译:车联网(IoV)已成为物联网(IoT)中智能交通不可或缺的数据感知和处理平台。车辆上安装的摄像头以及固定的路边摄像头用于为车联网用户和执法机构提供图像服务。对于此类取证服务,在保证车辆间数据传输效率的同时,确保车辆的安全性和隐私性非常重要。本文提出了一种用于车联网取证服务的轻量级激励认证方案(LIAS)。LIAS是在包含云层、雾层和用户层的三层架构上开发的。LIAS采用无配对无证书签密、假名更新机制、激励机制等方式,高效实现安全的匿名认证。我们进行正确性和安全性分析,以及性能分析和评估,以验证LIAS的高安全性和效率。实验结果表明,LIAS的通信和计算开销以及消息延迟和丢包远低于现有技术。从业者须知——本文的出发点是智能交通车联网取证服务的安全和隐私问题。我们的目标是提高车辆的安全性和隐私性,同时保证车辆之间数据传输的轻量级和激励性。引入雾辅助车联网,充分利用近用户边缘设备的能力以及雾节点与设备之间的连接。然而,在确保车辆安全和隐私方面仍面临困难。此外,由于无线通信不可避免的缺陷,车辆的信息传播可以很容易地被监控。因此,在取证服务期间,必须保证车辆的安全和隐私,同时提高车辆数据传输的效率。为此,该文提出一种基于免配对技术开发的面向车联网取证业务的轻量级条件匿名认证方案,以实现高效的安全匿名认证。本文还设计了一种用户追踪机制、激励机制和假名更新机制,以实现车联网安全有效的取证服务。

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