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位置轨迹大数据的安全分享、发布需求离不开位置轨迹隐私保护技术支持。在差分隐私出现之前,K-匿名及其衍生模型为位置轨迹隐私保护提供了一种量化评估的手段,但其安全性严重依赖于攻击者所掌握的背景知识,当有新的攻击出现时模型无法提供完善的隐私保护。差分隐私技术的出现有效地弥补了上述问题,越来越多地应用于轨迹数据隐私发布领域中。该文对基于差分隐私理论的轨迹隐私保护技术进行了研究与分析,重点介绍了差分隐私模型下位置直方图、轨迹直方图等空间统计数据发布方法,差分隐私模型下轨迹数据集发布方法,以及连续轨迹实时发布隐私保护模型。与此同时,在对现有方法对比分析的基础上,提出了未来的重点发展方向。
相似文献2.
针对权重社会网络发布隐私保护中的弱保护问题,提出一种基于差分隐私模型的随机扰动方法可实现边及边权重的强保护。设计了满足差分隐私的查询模型-WSQuery,WSQuery模型可捕获权重社会网络的结构,以有序三元组序列作为查询结果集;依据WSQuery模型设计了满足差分隐私的算法-WSPA,WSPA算法将查询结果集映射为一个实数向量,通过在向量中注入Laplace噪音实现隐私保护;针对WSPA算法误差较高的问题提出了改进算法-LWSPA,LWSPA算法对查询结果集中的三元组序列进行分割,对每个子序列构建满足差分隐私的算法,降低了误差,提高了数据效用。实验结果表明,提出的隐私保护方法在实现隐私信息的强保护同时使发布的权重社会网络仍具有可接受的数据效用。 相似文献
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为了解决基于位置的服务(Location Based Service,LBS)在收集用户位置数据时造成的隐私泄露,提出一种本地化差分隐私位置发布模型.首先,该模型采用了灵活的位置隐私保护方案(个性化隐私设置),即由用户选择已设定的多种隐私策略或定制隐私策略,在此基础上设计了定制隐私策略位置扰动算法(Customized Privacy policy Location Perturbation algorithm,CPLP);其次,提出并设计一种基于隐马尔可夫模型的时序关联位置隐私发布算法(Temporal Relational Location Privacy publishing algorithm,TRLP),解决发布时序位置时产生的隐私泄露;最后,在GeoLife数据集和Gowalla数据集上通过对比实验验证了该模型的有效性. 相似文献
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为解决轨迹差分隐私保护中存在的隐私预算与服务质量等问题,提出了一种融合预测扰动的轨迹差分隐私保护机制。首先,利用马尔可夫链和指数扰动方法预测满足差分隐私和时空安全的扰动位置,并引入服务相似地图检测该位置的可用性;如果预测成功,则直接采用预测位置替代差分扰动的位置,以降低连续查询的隐私开销并提高服务质量。在此基础上,设计基于w滑动窗口的轨迹隐私预算分配机制,确保轨迹中任意连续的w次查询满足ε-差分隐私,解决连续查询的轨迹隐私问题。此外,基于敏感度地图设计一种隐私定制策略,通过自定义语义位置的隐私敏感度,实现隐私预算的量身定制,从而进一步提高其利用率。最后,利用真实数据集对所提方案进行实验分析,结果显示所提方案提供了更好的隐私保护水平和服务质量。 相似文献
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随着智能终端的普及和无线通信技术的发展,基于位置的服务已渗入到人们的日常生活当中.这些服务在给人们的日常生活带来便利的同时,也带来隐私泄漏的风险.针对轨迹数据的推理攻击不仅可分析出目标用户的家庭住址、工作地点等敏感位置信息,甚至可推测出用户的生活习惯、健康状态、宗教信仰等隐私信息.轨迹隐私能否得到妥善保护已成为制约移动互联网发展的瓶颈问题.本文对已有的轨迹隐私保护方法进行了分类描述,并分析已有工作的优缺点,最后指明未来的研究方向. 相似文献
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面向频繁模式挖掘的差分隐私保护研究综述 总被引:1,自引:0,他引:1
频繁模式挖掘是数据挖掘的一个基本问题,其模式本身和相应计数都有可能泄露隐私信息。当前,差分隐私通过添加噪音使数据失真,有效实现了隐私保护的目的。首先介绍了差分隐私保护模型的理论基础;其次,详细综述了差分隐私下3种典型的频繁模式挖掘方法的最新研究进展,并进行对比性分析;最后对未来的研究方向进行了展望。 相似文献
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段谟意 《智能计算机与应用》2016,(6)
为了更有效地保护用户的轨迹隐私,提出综合位置大数据、移动社交网络服务各自的特点,从网络技术、心理学、社会学、信息学等多角度,对用户位置与行为模式之间映射后的个性向量模糊化,全方位量化分析影响位置大数据的移动社交网络服务(Mobile social network servicebased on location big data,MSNSLBD)的属性,重新给出了轨迹隐私的定义,最后对MSNSLBD的研究方向及需要解决的关键技术问题进行了展望. 相似文献
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This meta-analysis investigates privacy concerns and literacy as predictors of use of online services and social network sites (SNSs), sharing information, and adoption of privacy protective measures. A total of 166 studies from 34 countries (n = 75,269) were included in the analysis. In line with the premise of privacy paradox, privacy concerns did not predict SNS use. However, users concerned about privacy were less likely to use online services and share information and were more likely to utilize privacy protective measures. Except for information sharing, the relationships were comparable for intentions and behavior. Analyses also confirm the role that privacy literacy plays in enhancing use of privacy protective measures. The findings can be generalized across gender, cultural orientation, and national legal systems. 相似文献
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啄木鸟 《信息安全与通信保密》2001,(8):79
前一阵子,笔者办事完毕,途经京城老字号大栅栏一条街,只见各家商号门庭若市,人声鼎沸,商品琳琅满目,购者如潮。笔者此时闲来无事,便闲逛起街来。 忽然有一妇人凑过身子,低声搭话:“窃听器,要吗?”笔者略一吃惊,心想这玩艺儿也有人卖?见笔者有拒绝之意,此妇人 相似文献
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Privacy Preserving Data Mining 总被引:4,自引:0,他引:4
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William J. Buchanan Zbigniew Kwecka Elias Ekonomou 《Mobile Networks and Applications》2013,18(5):728-737
The move towards service-oriented architectures and the increasing usage of mobile devices to access such services are two of the major changes in modern computing. Information about the user, their location and their trajectory can provide additional context information to a service, leading to useful applications such as directing a user to the nearest bus stop and displaying which buses are due to arrive in the next minutes. While this type of information can be useful, when the offered services are trusted, it also introduces privacy issues relating to gathering of location information for non-trusted applications like location-based marketing or user behaviour profiling. Users can limit their location information provided to a service but these controls are simple, making it important for the user to understand how their location information is being used by services. This paper reviews some of the methods currently being proposed to reduce the impact of location tracking on user privacy, and presents a novel encryption method for preserving the location and trajectory path of a user using Privacy-Enhancing Technologies. 相似文献
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Privacy Preserving Data Mining 总被引:1,自引:0,他引:1
In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties
owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary
information. Our work is motivated by the need both to protect privileged information and to enable its use for research or
other purposes.
The above problem is a specific example of secure multi-party computation and, as such, can be solved using known generic
protocols. However, data mining algorithms are typically complex and, furthermore, the input usually consists of massive data
sets. The generic protocols in such a case are of no practical use and therefore more efficient protocols are required. We
focus on the problem of decision tree learning with the popular ID3 algorithm. Our protocol is considerably more efficient
than generic solutions and demands both very few rounds of communication and reasonable bandwidth. 相似文献
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G. M. Køien 《Wireless Personal Communications》2007,40(3):443-455
In this paper, we investigate location- and identity privacy issues related to the access procedures. The investigation includes
subscriber identity management, mobility management at the link layer and the security setup (authentication and key agreement)
procedures. The paper also presents a Privacy Enhanced Mobile Authentication and Key Agreement (PEMAKA) protocol that illustrates
the concepts and demonstrates that future mobile systems can provide both improved access security and enhanced subscriber
privacy. 相似文献
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