抵御背景知识推理攻击的服务相似性位置k匿名隐私保护方法

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抵御背景知识推理攻击的服务相似性位置k匿名隐私保护方法

更新时间：2025-07-09

- 抵御背景知识推理攻击的服务相似性位置k匿名隐私保护方法
- Issue 1, Pages: 8-18(2020)
- 作者机构：
  
  兰州交通大学电子与信息工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP309
- Published：2020
- 稿件说明：
移动端阅览
[J]. 2020, (1): 8-18.
DOI：

[J]. 2020, (1): 8-18. DOI：

摘要

针对已有位置k匿名方法不能很好地权衡位置隐私和服务可用性之间的关系、易于遭受背景知识推理攻击、资源开销大的问题

提出了一种抵御推理攻击的服务相似性位置k匿名隐私保护方法。通过引入服务相似性生成标签相似地图

并根据服务相似度将用户所在分区与其他分区合并

生成满足用户服务质量需求的匿名候选区。为抵御推理攻击

在选择k匿名集时使用位置熵对攻击者的背景知识进行量化以生成熵最大的k匿名集。在生成k匿名集时

采用贪心策略并在匿名集随机选取一个位置点请求服务以降低资源开销。安全性分析和实验结果表明:相较于已有位置k匿名方法

在相同条件下

所提方法的隐私保护度和服务可用性平均提高了48.49%和60.01%

时间开销和通信开销平均降低了86.12%和66.57%。所提方法在隐私保护度、服务可用性和资源开销之间取得了更好的权衡

且可有效抵御背景知识推理攻击。

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