scholarly journals KLPPS: A k-Anonymous Location Privacy Protection Scheme via Dummies and Stackelberg Game

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Dongdong Yang ◽  
Baopeng Ye ◽  
Wenyin Zhang ◽  
Huiyu Zhou ◽  
Xiaobin Qian

Protecting location privacy has become an irreversible trend; some problems also come such as system structures adopted by location privacy protection schemes suffer from single point of failure or the mobile device performance bottlenecks, and these schemes cannot resist single-point attacks and inference attacks and achieve a tradeoff between privacy level and service quality. To solve these problems, we propose a k-anonymous location privacy protection scheme via dummies and Stackelberg game. First, we analyze the merits and drawbacks of the existing location privacy preservation system architecture and propose a semitrusted third party-based location privacy preservation architecture. Next, taking into account both location semantic diversity, physical dispersion, and query probability, etc., we design a dummy location selection algorithm based on location semantics and physical distance, which can protect users’ privacy against single-point attack. And then, we propose a location anonymous optimization method based on Stackelberg game to improve the algorithm. Specifically, we formalize the mutual optimization of user-adversary objectives by using the framework of Stackelberg game to find an optimal dummy location set. The optimal dummy location set can resist single-point attacks and inference attacks while effectively balancing service quality and location privacy. Finally, we provide exhaustive simulation evaluation for the proposed scheme compared with existing schemes in multiple aspects, and the results show that the proposed scheme can effectively resist the single-point attack and inference attack while balancing the service quality and location privacy.

2019 ◽  
Vol 28 (09) ◽  
pp. 1950147
Author(s):  
Lei Zhang ◽  
Jing Li ◽  
Songtao Yang ◽  
Yi Liu ◽  
Xu Zhang ◽  
...  

The query probability of a location which the user utilizes to request location-based service (LBS) can be used as background knowledge to infer the real location, and then the adversary may invade the privacy of this user. In order to cope with this type of attack, several algorithms had provided query probability anonymity for location privacy protection. However, these algorithms are all efficient just for snapshot query, and simply applying them in the continuous query may bring hazards. Especially that, continuous anonymous locations which provide query probability anonymity in continuous anonymity are incapable of being linked into anonymous trajectories, and then the adversary can identify the real trajectory as well as the real location of each query. In this paper, the query probability anonymity and anonymous locations linkable are considered simultaneously, then based on the Markov prediction, we provide an anonymous location prediction scheme. This scheme can cope with the shortage of the existing algorithms of query probability anonymity in continuous anonymity locations difficult to be linked, and provide query probability anonymity service for the whole process of continuous query, so this scheme can be used to resist the attack of both of statistical attack as well as the infer attack of the linkable. At last, in order to demonstrate the capability of privacy protection in continuous query and the efficiency of algorithm execution, this paper utilizes the security analysis and experimental evaluation to further confirm the performance, and then the process of mathematical proof as well as experimental results are shown.


2019 ◽  
Vol 148 ◽  
pp. 142-150 ◽  
Author(s):  
Hao Wang ◽  
Guangjie Han ◽  
Lina Zhou ◽  
James Adu Ansere ◽  
Wenbo Zhang

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 121
Author(s):  
Mulugeta Kassaw Tefera ◽  
Xiaolong Yang

The wide-ranging application of location-based services (LBSs) through the use of mobile devices and wireless networks has brought about many critical privacy challenges. To preserve the location privacy of users, most existing location privacy-preserving mechanisms (LPPMs) modify their real locations associated with different pseudonyms, which come at a cost either in terms of resource consumption or quality of service, or both. However, we observed that the effect of resource consumption has not been discussed in existing studies. In this paper, we present the user-centric LPPMs against location inference attacks under the consideration of both service quality and energy constraints. Moreover, we modeled the precision-based and dummy-based mechanisms in the context of an existing LPPM framework, and also extended the linear program solutions applicable to them. This study allowed us to specify the LPPMs that decreased the precision of exposed locations or generated dummy locations of the users. Based on this, we evaluated the privacy protection effects of optimal location obfuscation function against an adversary's inference attack function using real mobility datasets. The results indicate that dummy-based mechanisms provide better achievable location privacy under a given combination of service quality and energy constraints, and once a certain level of privacy is reached, both the precision-based and dummy-based mechanisms only perturb the exposed locations. The evaluation results also contribute to a better understanding for the LPPM design strategies and evaluation mechanism as far as the system resource utilization and service quality requirements are concerned.


PLoS ONE ◽  
2017 ◽  
Vol 12 (8) ◽  
pp. e0182232 ◽  
Author(s):  
Haitao Zhang ◽  
Chenxue Wu ◽  
Zewei Chen ◽  
Zhao Liu ◽  
Yunhong Zhu

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2074 ◽  
Author(s):  
Qiuhua Wang ◽  
Jiacheng Zhan ◽  
Xiaoqin Ouyang ◽  
Yizhi Ren

Wireless Sensor Networks (WSNs) have been widely deployed to monitor valuable objects. In these applications, the sensor node senses the existence of objects and transmitting data packets to the sink node (SN) in a multi hop fashion. The SN is a powerful node with high performance and is used to collect all the information sensed by the sensor nodes. Due to the open nature of the wireless medium, it is easy for an adversary to trace back along the routing path of the packets and get the location of the source node. Once adversaries have got the source node location, they can capture the monitored targets. Thus, it is important to protect the source node location privacy in WSNs. Many methods have been proposed to deal with this source location privacy protection problem, and most of them provide routing path diversity by using phantom node (PN) which is a fake source node used to entice the adversaries away from the actual source node. But in the existing schemes, the PN is determined by the source node via flooding, which not only consumes a lot of communication overhead, but also shortens the safety period of the source node. In view of the above problems, we propose two new grid-based source location privacy protection schemes in WSNs called grid-based single phantom node source location privacy protection scheme (SPS) and grid-based dual phantom node source location privacy protection scheme (DPS) in this paper. Different from the idea of determining the phantom node by the source node in the existing schemes, we propose to use powerful sink node to help the source node to determine the phantom node candidate set (PNCS), from which the source node randomly selects a phantom node acting as a fake source node. We evaluate our schemes through theoretical analysis and experiments. Experimental results show that compared with other schemes, our proposed schemes are more efficient and achieves higher security, as well as keeping lower total energy consumption. Our proposed schemes can protect the location privacy of the source node even in resource-constrained wireless network environments.


2018 ◽  
Vol 189 ◽  
pp. 10013
Author(s):  
Tao Feng ◽  
Xudong Wang ◽  
Xinghua Li

Location based Service (the Location - -based Service, LBS) is a System is to transform the existing mobile communication network, wireless sensor networks, and Global Positioning System (Global Positioning System, GPS) with the combination of information Service mode, the general improvement in Positioning technology and the high popularity of mobile intelligent terminals, led to the growing market of LBS. This article from the perspective of LBS service privacy security, mainly studies the LBS location privacy protection scheme based on cipher text search, in LBS service location privacy and search information privacy issues, focus on to design the scheme, based on the cryptography in LBS service privacy protection issues in the process, this paper fully and secret cipher text search characteristics, design a new privacy protection of LBS service model, and expounds the system structure and working principle of model, defines the security properties of the privacy protection model and security model, Under the specific security assumptions, the new location privacy protection scheme based on lbspp-bse (LBS location privacy protection based on searchable encryption) is implemented.


2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hongtao Li ◽  
Xingsi Xue ◽  
Zhiying Li ◽  
Long Li ◽  
Jinbo Xiong

The widespread use of Internet of Things (IoT) technology has promoted location-based service (LBS) applications. Users can enjoy various conveniences brought by LBS by providing location information to LBS. However, it also brings potential privacy threats to location information. Location data that contains private information is often transmitted among IoT networks in LBS, and such privacy information should be protected. In order to solve the problem of location privacy leakage in LBS, a location privacy protection scheme based on k -anonymity is proposed in this paper, in which the Geohash coding model and Voronoi graph are used as grid division principles. We adopt the client-server-to-user (CS2U) model to protect the user’s location data on the client side and the server side, respectively. On the client side, the Geohash algorithm is proposed, which converts the user’s location coordinates into a Geohash code of the corresponding length. On the server side, the Geohash code generated by the user is inserted into the prefix tree, the prefix tree is used to find the nearest neighbors according to the characteristics of the coded similar prefixes, and the Voronoi diagram is used to divide the area units to complete the pruning. Then, using the Geohash coding model and the Voronoi diagram grid division principle, the G-V anonymity algorithm is proposed to find k neighbors in an anonymous area so that the user’s location data meets the k -anonymity requirement in the area unit, thereby achieving anonymity protection of location privacy. Theoretical analysis and experimental results show that our method is effective in terms of privacy and data quality while reducing the time of data anonymity.


Sign in / Sign up

Export Citation Format

Share Document