Chinese Journal of Network and Information Security ›› 2016, Vol. 2 ›› Issue (12): 1-11.doi: 10.11959/j.issn.2096-109x.2016.00088
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Ming-jie MA1,Yue-jin DU1,2,Feng-hua LI1,IUJia-wen L3
Revised:
2016-11-06
Online:
2016-12-01
Published:
2016-12-28
Supported by:
CLC Number:
Ming-jie MA,Yue-jin DU,Feng-hua LI,IUJia-wen L. Review of semantic-based privacy-preserving approaches in LBS[J]. Chinese Journal of Network and Information Security, 2016, 2(12): 1-11.
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类别 | 方法 | 优点 | 缺点 |
语义感知[ | 能抵抗空间背景知识攻击 | 保护效果较差 | |
本体论[ | 攻击者很难辨别真实位置 | 未考虑路网情况 | |
树算法[ | 算法简单易理解 | 算法受内存大小限制 | |
Location diversity[ | 给出了语义位置概念,一定程度上保护现实生活的敏感位置 | 文章假设敏感位置是一个静态集合,可能会产生不符合现实情况的问题 | |
单点 | 特征提取[ | 在考虑位置流行度的基础上,用户可预先定义列表 | 未考虑路网情况 |
SALS[ | 隐私度高 | 计算开销大 | |
Voronoi图[ | 解决路网环境和P2P环境的隐私保护问题,有效解决单路段攻击 | 未考虑连续LBS情况以及用户上下文信息 | |
语义位置模糊匿名[ | 易实现 | 依靠可信第三方 | |
贝叶斯[ | 实现贝叶斯方法建模位置语义 | 依靠可信第三方 | |
B.E.S[ | 定义了停走模型 | 特征较为简单,保护力度不够 | |
语义匿名[ | 可抵御相似性攻击 | 保护强度受匿名集大小影响 | |
轨迹 | 区域EMD[ | 采用停留时间模型,考虑语义位置选取能够很好地保护敏感位置 | 未考虑路网信息保护程度和服务质量受敏感位置分布的影响 |
树算法[ | 能抵御推断攻击 | 计算开销大 | |
相似性聚类[ | 不依赖真实用户轨迹,可有效保护种子用户的隐私 | 未考虑轨迹中的时间因素 |
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