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基于位置的隐私保护日益重要，k-匿名技术是保护位置隐私的有效方法之一。大多数现有方案根据位置的单一属性生成匿名集，攻击者很容易根据背景知识推断出匿名集中的真实位置。为了解决这个问题，提出一种基于多属性决策的双k-匿名位置隐私保护策略（dual k-anonymous location privacy-preserving scheme with multi-attribute decision-making,DKMD），来解决基于位置的服务（location-based services,LBS）场景中的隐私问题。首先，提出一个边缘缓存策略来提高数据访问效率，减少第三方匿名器的隐私威胁；其次，设计双k-匿名策略，在用户向边缘缓存器或边缘缓存器向LBS服务器发起查询之前，都生成一个匿名集以防止用户位置被识别，并在边缘缓存器向LBS服务器发起查询前，采用多属性决策生成一个边缘匿名集，从而进一步提高匿名集的安全性；最后，通过在真实轨迹数据集上的对比实验，测试位置熵、位置分散度、缓存效率与运算时间等性能指标。实验结果表明：DKMD能够在保护用户位置隐私的同时，提高整个系统的数据传输速率。
Abstract：Location-based privacy protection is increasingly important, and k-anonymity technique is an effective method for protecting location privacy. Most existing schemes generate anonymous sets based on a single attribute of location, making it easy for attackers to infer real locations within the anonymous set using background knowledge. To address this issue, a dual k-anonymous location privacy-preserving scheme with multi-attribute decision-making(DKMD) is proposed to solve privacy problems in location-based services(LBS) scenarios. Firstly, an edge caching strategy is proposed to improve data access efficiency and reduce privacy threats from third-party anonymizers.Secondly, a dual k-anonymity scheme is designed: an anonymous set is generated before the user queries the edge cache or before the edge cache queries the LBS server to prevent user location identification. Before the edge cache queries the LBS server, multi-attribute decision-making is adopted to generate an edge anonymous set, thereby further enhancing the security of the anonymous set. Finally, comparative experiments are conducted on real trajectory datasets to evaluate performance metrics including location entropy, location dispersion, caching efficiency, and computational time. Results demonstrate that the proposed DKMD framework enhances overall system data transmission rates while protecting user location privacy.
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基本信息:
DOI：10.12194/j.ntu.20241111001
中图分类号:TP309
引用信息:
[1]陈雪祺,章静,林雨薇,等.基于多属性决策的双k-匿名位置隐私保护策略[J].南通大学学报(自然科学版),2025,24(04):10-20.DOI:10.12194/j.ntu.20241111001.
基金信息:
国家自然科学基金青年科学基金项目(61902069); 福建省自然科学基金面上项目(2025J01380,2021J011068)