Department of Computer Science, Superior University, Lahore, Pakistan.
Department of Computer Science, New Uzbekistan University, Tashkent, Uzbekistan.
PLoS One. 2024 Oct 31;19(10):e0310267. doi: 10.1371/journal.pone.0310267. eCollection 2024.
Towards the intelligent transportation systems, Location Based Service (LBS) are widely engaged in Vehicular Ad Hoc Networks (VANETs) that are becoming as significant application that change the human driving experience in today's world. LBS systems facilitate the users with intelligent services by collecting an accurate location information. Due to the frequent exchange rate of the location information in an open environment, VANETs are inherently susceptible to privacy and security attacks. In past, many schemes have been proposed to ensure the privacy and security of exchanged location information; but fail to deploy in practical VANETs. At the same time, system efficiency is compromised which is another primary requirement of VANETs. Leveraging the semi-decentralized and lightweight nature of consortium blockchain technology, and Certificateless conditional privacy protection scheme to reduce the node authentication overhead, this paper introduces Consortium Blockchain assisted Certificateless Conditional Privacy Protection scheme to address the aforementioned challenges. Additionally, the proposed scheme has ability to develop anonymous regions for a particular time stamp ensuring the location privacy of vehicles. Rigorous security analysis and experiments show the practicality and resilience to various attack models, and achieve ADP 83% with maximum malicious attacks. Comparing with existing state of the art methods, the proposed scheme exhibits the privacy improvement and low computational complexity.
面向智能交通系统,基于位置的服务(LBS)广泛应用于车联网(VANET),这是当今改变人类驾驶体验的重要应用。LBS 系统通过收集准确的位置信息为用户提供智能服务。由于在开放环境中位置信息的频繁交换率,VANET 容易受到隐私和安全攻击。在过去,已经提出了许多方案来确保交换位置信息的隐私和安全;但未能在实际的 VANET 中部署。同时,系统效率受到影响,这是 VANET 的另一个主要要求。利用联盟区块链技术的半分散和轻量级特性,以及无证书条件隐私保护方案来减少节点认证开销,本文引入了联盟区块链辅助的无证书条件隐私保护方案来解决上述挑战。此外,该方案还能够为特定时间戳开发匿名区域,以确保车辆的位置隐私。严格的安全分析和实验表明,该方案具有抵御各种攻击模型的实用性和弹性,并在最大恶意攻击下达到了 ADP83%。与现有最先进的方法相比,该方案在隐私保护和低计算复杂度方面表现出了优势。