移动互联网中的位置隐私保护研究

全面归纳了移动互联网中位置隐私保护的相关研究工作,总结了位置服务和定位服务中的威胁模型。然后,详细介绍了现有基于位置服务的隐私保护技术,分析了其在抗隐私攻击和位置隐私适用性方面的优缺点,并阐述了定位服务中位置隐私问题的本质、威胁和解决方法。最后指出了需要进一步研究的问题。     

基于差分隐私模型的位置轨迹发布技术研究

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。     

基于差分隐私的轨迹隐私保护方法

针对现有的轨迹隐私保护模型大多难以抵御复杂背景知识攻击的问题,本文提出了一种基于差分隐私的轨迹隐私保护方法.首先结合地理不可区分机制对原始轨迹数据添加半径受限的拉普拉斯噪音;其次构造数据映射模型将原始数据和噪音数据映射到新的发布位置,使攻击者无法获取真实轨迹数据;接着应用最优数据映射函数发布最优的轨迹位置以提高发布数据的可用性;最后利用差分隐私抵御非敏感信息推理攻击,进一步保护用户隐私.实验结果表明,本文算法既能有效保护轨迹数据中用户的隐私,也能保证数据的可用性.     

LBS中面向协同位置隐私保护的群组最近邻查询

在分析现有群组最近邻查询中位置隐私保护的基础上,提出LBS中一种面向位置隐私保护的群组最近邻查询方法。该方法采用分布式系统结构,克服了集中式匿名系统结构所存在通信瓶颈和攻击重点的缺陷。在此基础上根据用户群组的运动状态信息,提出使用位置随机扰动和门限秘密共享的Paillier密码系统来安全地计算用户群组的质心位置。于是将用户群组的最近邻查询转换为此质心的最近邻查询。与现有的相关工作相比,理论分析表明所提有关方案能够在有效抵御现有的距离交叉攻击和共谋攻击下,实现灵活的群组最近邻查询,同时耗费较低的网络资源。     

基于LBS的位置隐私保护方案综述

LBS随移动互联网的发展逐步进入人们的日常生活。文章针对位置隐私保护这一问题,介绍了位置隐私保护方案的系统结构,从4个不同的技术方向研究了位置隐私保护方案,总结了现有的位置隐私保护方案,并对未来的研究方向进行了展望。     

基于Hilbert填充曲线的海洋无线传感网源节点位置隐私保护方法

节点位置保护对于海洋无线传感器网络(MWSNs)至关重要,尤其是对于无人值守的环境。然而,由于大多数静态部署,传感器的能量、存储和通信能力的限制,MWSNs容易受到各种位置(和衍生)攻击的影响。该文从攻击和防御两个方面研究节点位置隐私保护问题。首先,针对两种重要节点(包括基站和源节点)提出了一种新的二相定位攻击,它可以在少量的本地无线传输监视中找到基站节点,反向跟踪源节点的位置。与现有方法不同,提出的攻击根据传输方向确定节点位置,从而突破现有的防御。然后,为了抵御这种攻击,该文设计了一种基于Hilbert填充曲线的传感器网络路由节点位置隐私保护方法(HLPS)。攻防理论分析与对抗实验表明,该方法能够保护目标节点的位置隐私,具有较小的通信和计算开销。     

基于Montgomery型椭圆曲线密码的RFID安全认证方案

针对现有基于椭圆曲线密码（elliptic curve cryptography,ECC）体制的 RFID（radio frequency identification device）安全认证方案不能满足相互认证、隐私保护和前向安全性等要求,提出一种基于Montgomery型椭圆曲线密码的认证方案。利用Montgomery型椭圆曲线来降低计算量,并提供标签和服务器之间的相互认证,具有匿名性和前向安全性。通过分析表明,该方案能够抵抗重放攻击、标签伪装攻击、服务器欺骗攻击、DoS攻击、位置跟踪攻击和克隆攻击。与现有方案相比,该方案在保证较低的内存、计算和通信需求的情况下,提供了较高的安全性能,能够满足RFID系统的安全性要求。     

连续服务请求下基于假位置的用户隐私增强方法

基于假位置的隐私保护方案在为用户提供准确位置服务查询结果的同时,还无需第三方和共享密钥。然而,当用户连续请求位置服务时,由于现有保护单次查询的假位置方案未考虑相邻位置集合间的时空关系,使攻击者能推断出假位置,降低用户的位置隐私保护等级。针对上述问题,采用现有假位置方案生成候选假位置,并通过连续合理性检查和单次隐私增强对其进行筛选,提出一个适用于连续请求的假位置隐私保护增强方法。安全性分析表明,所提方法能保证连续请求中形成的移动路径在时空上不可区分,有效保护连续请求中的用户位置隐私。大量实验表明,所提方法在不增加用户计算开销的同时,与采用的候选假位置生成方案相比,还能提高用户单次查询的隐私保护等级。     

移动互联网服务的隐私保护机制

探讨了考虑背景信息的位置和查询隐私保护方案,如基于背景信息的虚假位置k-匿名方案、同时保护位置和兴趣的隐私保护方案、基于交互的隐私保护方案,还探讨了基于用户隐私链拆分的实名认证和身份隐私保护策略;认为在避免可信第三方参与,敌手能够获取到背景信息的前提下,能够实现对用户身份、位置和查询隐私的保护,达到信任机制和隐私保护的有机结合将是未来隐私保护发展的趋势。     

面向ZigBee网络节点安全定位的消息签名方案

针对ZigBee网络节点定位中消息的安全性问题,该文提出一种带隐私保护的消息签名方案。方案基于椭圆曲线(ECC)上的无双线性对运算,设计了带身份隐私保护的定位请求消息签名算法和坐标隐私保护的定位参照消息签名算法。理论证明了所提方案可抵御伪造攻击、重放攻击等多种外部攻击,同时具备隐私保护、身份追踪等功能。性能分析结果表明,与同类方案相比,所提方案计算开销和通信开销均具有优势。     

CP-ABE based users collaborative privacy protection scheme for continuous query

In location-based services (LBS),as the untrusted LBS server can be seen as an adversary,and it can utilize the attribute as background knowledge to correlate the real location of the user in the set of uncertain locations.Then the adversary can gain the location privacy when the user enjoys the snapshot and continuous query through the correlation inference attack.In order to cope with this attack,the main scheme in privacy protection is to generalize the attribute and achieve attribute anonymity.However,algorithms of this type usually assumes a trusted third party (TTP) which provides the service of similarity attribute finding and comparing,and it is unpractical in the real environment,as the TTP may become the point of attack or the bottleneck of service and it cannot be considered as the trusted one all the time.Thus,to cope with the correlation inference attack as well as the semi-trusted third party,ciphertext policy attribute based encryption (CP-ABE) and users collaboration based attribute anonymous scheme was proposed.In this scheme,the user coupled achieve location and attribute anonymity.Furthermore,this scheme could also provide security for attacks from the semi-trusted third party as well as semi-trusted collaborative users.At last,security analysis and the experiment results further verify the effectiveness of privacy protection and the efficiency of algorithm execution.     

面向LBS的隐私保护模型及方案

首先,提出一种基于中心服务器结构的位置隐私保护模型,然后,针对该模型设计了一种基于伪随机置换的位置隐私保护方案,此方案借鉴k-匿名技术、秘密信息检索技术的设计理念和方法,实现了完美匿名和基于位置的盲查询。最后,证明此方案具备不可追踪性和不可关联性等安全属性,并对方案的效率问题进行了分析。     

A novel attributes anonymity scheme in continuous query

In location-based service (LBS), the un-trusted LBS server can preserve lots of information about the user. Then the information can be used as background knowledge and initiated the inference attack to get user’s privacy. Among the background knowledge, the profile attribute of users is the especial one. The attribute can be used to correlate the real location in uncertain location set in both of the snapshot and continuous query, and then the location privacy of users will be revealed. In most of the existing scheme, the author usually assumes a trusted third party (TTP) to achieve the profile anonymity. However, as the TTP disposes all anonymous procedure for each user, it will become the center of attacks and the bottleneck of the query service. Furthermore, the TTP may be curious about user’s privacy just because of the commercial consideration. In order to deal with the inference attack and remedy the drawback of TTP scheme, we propose a similar attributes anonymous scheme which based on the CP-ABE, and with the help of center server and collaborative users, our scheme can resist the inference attack as well as the privacy detection of any entity in the service of query. At last, security analysis and experimental results further verify the effectiveness of our scheme in privacy protection as well as efficiency of the algorithm execution.     

Location privacy preserving scheme against attack from friends in SNS

In order to enrich the performance of the user's location information and to meet the diverse needs of users,a location privacy protection scheme based on attribute encryption was designed,which provided precise,more accurate,fuzzy and private four modes to manage the location information.The scheme was based on the algorithm of WT-CP-ABE.The location information was divided into three parts according to a close friend of grade,then the key infor-mation and position information was encrypted with attribute-based encryption and symmetric encryption method respec-tively and the ciphertext was published to the social network.The security of the scheme is analyzed,which shows that the scheme has the advantage of user attribute information confidentiality,data confidentiality and can resist the collusion attack.     

Trajectory differential privacy protection mechanism based on prediction and sliding window

To address the issues of privacy budget and quality of service in trajectory differential privacy protection,a trajectory differential privacy mechanism integrating prediction disturbance was proposed.Firstly,Markov chain and exponential perturbation method were used to predict the location which satisfies the differential privacy and temporal and spatial security,and service similarity map was introduced to detect the availability of the location.If the prediction was successful,the prediction location was directly used to replace the location of differential disturbance,to reduce the privacy cost of continuous query and improve the quality of service.Based on this,the trajectory privacy budget allocation mechanism based on w sliding window was designed to ensure that any continuous w queries in the trajectory meet the ε-differential privacy and solve the trajectory privacy problem of continuous queries.In addition,a privacy customization strategy was designed based on the sensitivity map.By customizing the privacy sensitivity of semantic location,the privacy budget could be customized to improve its utilization.Finally,the validity of the scheme was verified by real data set experiment.The results illustrate that it offers the better privacy and quality of service.     

Achieving efficient location privacy protection based on cache

With the development of mobile Internet and the popularization of intelligent terminals,location based services(LBS) has been widespread in navigation,social network and other fields.Due to the sensitivity of personal location information,data privacy protection related to location of mobile objects has become the hotspots of research.Considering the openness of the background information,and based on the information cache mechanism,a dummy selection algorithm was proposed to reduce the number of interactions between the user and the untrusted server and combine the k-anonymity to achieve efficient location privacy.Without relying on trusted third party,the scheme can prevent the attackers owned background information from inference attack,and the detail simulation results indicate its effectiveness and efficiency.     

AMOEBA: Robust Location Privacy Scheme for VANET

Communication messages in vehicular ad hoc networks (VANET) can be used to locate and track vehicles. While tracking can be beneficial for vehicle navigation, it can also lead to threats on location privacy of vehicle user. In this paper, we address the problem of mitigating unauthorized tracking of vehicles based on their broadcast communications, to enhance the user location privacy in VANET. Compared to other mobile networks, VANET exhibits unique characteristics in terms of vehicular mobility constraints, application requirements such as a safety message broadcast period, and vehicular network connectivity. Based on the observed characteristics, we propose a scheme called AMOEBA, that provides location privacy by utilizing the group navigation of vehicles. By simulating vehicular mobility in freeways and streets, the performance of the proposed scheme is evaluated under VANET application constraints and two passive adversary models. We make use of vehicular groups for anonymous access to location based service applications in VANET, for user privacy protection. The robustness of the user privacy provided is considered under various attacks.