With the popularity of mobile terminal equipment and wireless sensing network, the applications of mobile crowdsensing-based traffic violation monitoring are increasingly widely used. However, the enormous amount of sensing data with complex types brings a critical challenge to the limited bandwidth and storage space. Meanwhile, there is a serious risk of the sensing data and query privacy leakage in multi-requester/multi-user scenarios. To address the above issues, we propose a traffic violation image filtering and searching scheme for multi-requester/multi-user mobile crowdsensing, which achieves image content and user query privacy preservation. Specifically, we firstly consider the multiple factors that impaired image quality, then give the grading metric to perform image filtering and obtain high-quality images. In query and searching processes, we achieve that unshared key multi-requester/multi-user image retrieval without any image content and query privacy leakage. Moreover, our proposed scheme supports the malicious users’ accountability based on the revealed private keys, which significantly improve the security and reliability. Finally, we conduct the privacy analysis, which satisfies the privacy-preserving and security requirements. Experiment results on real-world dataset show that our approach to image filtering and searching is practical and effective.

随着移动终端设备和无线传感网络的普及，基于移动人群感知的交通违法监控应用越来越广泛。然而，海量复杂类型的传感数据给有限的带宽和存储空间带来了严峻的挑战。同时，在多请求者/多用户场景下，存在感知数据和查询隐私泄露的严重风险。针对上述问题，我们提出了一种多请求者/多用户移动人群感知的交通违章图像过滤和搜索方案，实现了图像内容和用户查询隐私保护。具体来说，我们首先考虑影响图像质量的多种因素，然后给出分级度量来进行图像过滤并获得高质量的图像。在查询和搜索过程中，我们实现了非共享密钥多请求者/多用户图像检索，没有任何图像内容和查询隐私泄露。此外，我们提出的方案支持基于公开私钥的恶意用户问责，显着提高了安全性和可靠性。最后，我们进行隐私分析，满足隐私保护和安全要求。在真实世界数据集上的实验结果表明，我们的图像过滤和搜索方法是实用且有效的。最后，我们进行隐私分析，满足隐私保护和安全要求。在真实世界数据集上的实验结果表明，我们的图像过滤和搜索方法是实用且有效的。最后，我们进行隐私分析，满足隐私保护和安全要求。在真实世界数据集上的实验结果表明，我们的图像过滤和搜索方法是实用且有效的。