在车联网场景中,现有基于位置服务的隐私保护方案存在不支持多种类型K近邻兴趣点的并行查询、难以同时保护车辆用户和位置服务提供商(Location-Based Service Provider,LBSP)两方隐私、无法抵抗恶意攻击等问题.为了解决上述问题,提出了一种保护两方隐私的多类型的路网K近邻查询方案MTKNN-MPP.将改进的k-out-of-n不经意传输协议应用于K近邻查询方案中,实现了在保护车辆用户的查询内容隐私和LBSP的兴趣点信息隐私的同时,一次查询多种类型K近邻兴趣点.通过增设车载单元缓存机制,降低了计算代价和通信开销.安全性分析表明,MTKNN-MPP方案能够有效地保护车辆用户的位置隐私、查询内容隐私以及LBSP的兴趣点信息隐私,可以保证车辆的匿名性,能够抵抗合谋攻击、重放攻击、推断攻击、中间人攻击等恶意攻击.性能评估表明,与现有典型的K近邻查询方案相比,MTKNN-MPP方案具有更高的安全性,且在单一类型K近邻查询和多种类型K近邻查询中,查询延迟分别降低了 43.23％～93.70％,81.07％～93.93％.
Abstract
In the Internet of vehicles scenario,existing location-based service privacy-preserving schemes have issues such as not supporting parallel query of multi-type K-nearest neighbor points of interest,difficulty to protect the privacy of both the in-vehi-cle users and the location-based service provider(LBSP),and unable to resist malicious attacks.In order to solve the above issues,a multi-type K-nearest neighbor query scheme with mutual privacy-preserving in road networks,named as MTKNN-MPP is pro-posed.By applying the improved k-out-of-n oblivious transfer protocol to the K-nearest neighbor query scheme,it is realized that multi-type K-nearest neighbor points of interest can be queried at a time while protecting the privacy of the query content of in-vehicle user and the privacy of the points of interest information of LBSP.The addition of the onboard unit caching mechanism re-duces computational cost and communication overhead.The security analysis shows that the MTKNN-MPP scheme can effective-ly protect the location privacy of in-vehicle users,query content privacy of in-vehicle users,and the privacy of points of interest in-formation of LBSP,which ensures the anonymity of the vehicle's identity and can resist malicious attacks such as collusion at-tacks,replay attacks,inference attacks,and man-in-the-middle attacks.Performance evaluation shows that compared with the existing typical K-nearest neighbor query schemes,the MTKNN-MPP scheme has higher security and the query latency in single-type K-nearest neighbor query and multi-type K-nearest neighbor query is reduced by 43.23％～93.70％and 81.07％～93.93％,respectively.
关键词
基于位置的服务/两方隐私保护/K近邻查询/不经意传输协议/车联网/多类型
Key words
Location-based service/Mutual privacy-preserving/K-nearest neighbor query/Oblivious transfer protocol/Internet of vehicles/Multi-type
维普
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