An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET
An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET
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DOI：
10.1155/2021/5302257
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发表时间：
2021-12
影响因子：
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通讯作者：
Zhihua Wang;Jiahao Liu;Chaoqi Guo;Shuailiang Hu;Yongjian Wang;Xiaolong Yang
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文献类型：
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作者：
Zhihua Wang;Jiahao Liu;Chaoqi Guo;Shuailiang Hu;Yongjian Wang;Xiaolong Yang
随着无线通信技术和车载自组织网络（VANET）的日益发展，以及各种传感器的不断普及，移动众感（MCS）模式在交通领域得到了广泛关注。作为目前流行的一种数据传感方式，它主要依靠无线传感设备来完成大规模、复杂的传感任务。但是，由于该场景下车辆具有高度的移动性，并且传感系统是开放的，即任何配备传感设备的车辆都可以加入系统，因此无法保证所有参与车辆的可信度。此外，恶意用户还会在传感系统中上传虚假数据，使传感数据不能满足传感任务的需要，严重时还会威胁交通安全。解决上述问题的方法有很多，如密码学、激励机制、声誉机制等。不幸的是，虽然这些方案保证了用户的可信度，但它们并没有考虑到数据的可靠性。此外，一些方案带来了大量的开销，一些使用集中式服务器管理架构，还有一些不适合VANET的场景。因此，本文首先提出了基于MCS-VANET架构的区块链，该区块链由参与车辆（pv）、路侧单元（rsu）、云服务器（CS）和区块链（BC）组成，然后设计了一个由三个阶段组成的恶意用户检测方案。在数据采集阶段，为了减少数据上传开销，充分考虑pv的历史信誉值，将数据聚合和机器学习技术相结合，并根据pv的历史数据质量评估结果确定数据上传比例。在数据质量评价阶段，提出了一种新的声誉计算模型，该模型包含四个指标：pv的声誉历史、数据的无偏性、pv的领导和pv的空间力量。在信誉更新阶段，为了实现信誉值的有效变化，引入logistic模型函数曲线，并将信誉更新结果存储在区块链中进行安全公示。最后，在实际数据集上，通过实验仿真和安全性分析验证了所提方案的可行性和有效性。与现有方案相比，该方案不仅降低了数据上传的成本，而且具有更好的性能。
With the increasing development of wireless communication technology and Vehicular Ad hoc Network (VANET), as well as the continuous popularization of various sensors, Mobile Crowdsensing (MCS) paradigm has been widely concerned in the field of transportation. As a currently popular data sensing way, it mainly relies on wireless sensing devices to complete large-scale and complex sensing tasks. However, since vehicles are highly mobile in this scenario and the sensing system is open, that is, any vehicle equipped with sensing device can join the system, the credibility of all participating vehicles cannot be guaranteed. In addition, malicious users will upload false data in the sensing system, which makes the sensing data not meet the needs of the sensing tasks and will threaten traffic safety in some serious cases. There are many solutions to the above problems, such as cryptography, incentive mechanism, and reputation mechanisms. Unfortunately, although these schemes guaranteed the credibility of users, they did not give much thought to the reliability of data. In addition, some schemes brought a lot of overhead, some used a centralized server management architecture, and some were not suitable for the scenario of VANET. Therefore, this paper firstly proposes the MCS-VANET architecture-based blockchain, which consists of participating vehicles (PVs), road side units (RSUs), cloud server (CS), and the blockchain (BC), and then designs a malicious user detection scheme composed of three phases. In the data collecting phase, to reduce the data uploading overhead, data aggregation and machine learning technologies are combined by fully considering the historical reputation value of PVs, and the proportion of data uploading is determined based on the historical data quality evaluation result of PVs. In the data quality evaluation phase, a new reputation computational model is proposed to effectively evaluate the sensing data, which contains four indicators: the reputation history of PVs, the data unbiasedness, the leadership of PVs, and the spatial force of PVs. In the reputation updating phase, to achieve the effective change of reputation values, the logistic model function curve is introduced and the result of the reputation updating is stored in the blockchain for security publicity. Finally, on real datasets, the feasibility and effectiveness of our proposed scheme are demonstrated through the experimental simulation and security analysis. Compared with existing schemes, the proposed scheme not only reduces the cost of data uploading but also has better performance.