A Hybrid Method of User Privacy Protection for Location Based Services

2013 ◽  
Author(s):  
Kenta Miura ◽  
Fumiaki Sato
Keyword(s):  
Hybrid Method ◽  
Privacy Protection ◽  
Location Based Services ◽  
User Privacy

Privacy-Preserving Spatial Trajectory Prediction Based on a Novel Matrix Representation

2016 ◽  
pp. 1693-1717
Author(s):  
Wen-Chen Hu ◽  
Naima Kaabouch ◽  
Hung-Jen Yang ◽  
S. Hossein Mousavinezhad
Keyword(s):  
Traffic Control ◽  
Privacy Protection ◽  
Matrix Representation ◽  
High Mobility ◽  
Location Based Services ◽  
Privacy Concern ◽  
User Privacy ◽  
Trajectory Prediction ◽  
Spatial Trajectory ◽  
Human Behavior Recognition

Since the introduction of iPhone in 2007, smartphones have become very popular (e.g., the number of worldwide smartphone sales has surpassed the number of PC sales in 2011). The feature of high mobility and small size of smartphones has created many applications that are not possible or inconvenient for PCs and servers, even laptops. Location-based services (LBS), one of mobile applications, have attracted a great attention recently. This research proposes a location-based service, which predicts a spatial trajectory based on the current and previous trajectories by using a novel matrix representation. Spatial trajectory prediction can be used in a variety of purposes such as travel recommendations and traffic control and planning, but at the same time, just like most location-based services, the user privacy concern is a major issue. Without rigorous privacy protection, users would be reluctant to use the service. The proposed method is simple but effective and user privacy is rigorously preserved at the same time because the trajectory prediction is performed at the user-side. Additionally, this research is not only useful but also pedagogical because it involves a variety of topics like (i) mobile computing, (ii) mobile security, and (iii) human behavior recognition.

scholarly journals Privacy Preserving Spatio-Temporal Databases Based on k-Anonymity

2020 ◽  
Vol 3 (SI1) ◽  
pp. SI82-SI94
Author(s):  
Anh Tuan Truong
Keyword(s):  
Data Mining ◽  
Privacy Protection ◽  
Location Privacy ◽  
Location Based Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Location Data ◽  
Related Information ◽  
Spatio Temporal ◽  
Location Privacy Protection

The development of location-based services and mobile devices has lead to an increase in the location data. Through the data mining process, some valuable information can be discovered from location data. In the other words, an attacker may also extract some private (sensitive) information of the user and this may make threats against the user privacy. Therefore, location privacy protection becomes an important requirement to the success in the development of location-based services. In this paper, we propose a grid-based approach as well as an algorithm to guarantee k-anonymity, a well-known privacy protection approach, in a location database. The proposed approach considers only the information that has significance for the data mining process while ignoring the un-related information. The experiment results show the effectiveness of the proposed approach in comparison with the literature ones.

scholarly journals A Method of Location Privacy Protection in Road Network Environment

2018 ◽  
Vol 173 ◽  
pp. 03048 ◽  
Author(s):  
Jianjun Wen ◽  
Zhao Li
Keyword(s):  
Privacy Protection ◽  
Road Network ◽  
Location Privacy ◽  
Location Based Services ◽  
Network Environment ◽  
User Privacy ◽  
Widespread Application ◽  
Location Service ◽  
Server Side ◽  
User Query

With the widespread application of location-based services, users 'privacy concerns have become the focus of users' attention. Based on the k-anonymity method and the SpaceTwist algorithm, this paper proposes a method of incremental inquiry user privacy protection. The method preliminarily anonymizes the user's location information and points of interest on the client side, On the anonymous server side, combining the road network environment with the latitude and longitude grid generates the minimum anonymous area of random loop, instead of the user initiating incremental inquiry to the location service provider, Anonymous zones ensure k-anonymity for mobile users and road information to protect user privacy. Security and experimental analysis show that this scheme can improve the effectiveness of user query service while meeting the privacy requirements of users.

scholarly journals Nonexposure Accurate LocationK-Anonymity Algorithm in LBS

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jinying Jia ◽  
Fengli Zhang
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
Location Based Services ◽  
Experimental Results ◽  
Location Information ◽  
User Privacy ◽  
Spatial Region ◽  
Exact Location ◽  
Current Location ◽  
Location Privacy Protection

This paper tackles location privacy protection in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. Location cloaking has been proposed and well studied to protect user privacy. It blurs the user’s accurate coordinate and replaces it with a well-shaped cloaked region. However, to obtain such an anonymous spatial region (ASR), nearly all existent cloaking algorithms require knowing the accurate locations of all users. Therefore, location cloaking without exposing the user’s accurate location to any party is urgently needed. In this paper, we present such two nonexposure accurate location cloaking algorithms. They are designed forK-anonymity, and cloaking is performed based on the identifications (IDs) of the grid areas which were reported by all the users, instead of directly on their accurate coordinates. Experimental results show that our algorithms are more secure than the existent cloaking algorithms, need not have all the users reporting their locations all the time, and can generate smaller ASR.

scholarly journals A Novel Location Privacy-Preserving Approach Based on Blockchain

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3519 ◽  
Author(s):  
Ying Qiu ◽  
Yi Liu ◽  
Xuan Li ◽  
Jiahui Chen
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
User Participation ◽  
Location Based Services ◽  
Third Party ◽  
User Privacy ◽  
Protection Method ◽  
Location Privacy Protection ◽  
Reward Mechanism

Location-based services (LBS) bring convenience to people’s lives but are also accompanied with privacy leakages. To protect the privacy of LBS users, many location privacy protection algorithms were proposed. However, these algorithms often have difficulty to maintain a balance between service quality and user privacy. In this paper, we first overview the shortcomings of the existing two privacy protection architectures and privacy protection technologies, then we propose a location privacy protection method based on blockchain. Our method satisfies the principle of k-anonymity privacy protection and does not need the help of trusted third-party anonymizing servers. The combination of multiple private blockchains can disperse the user’s transaction records, which can provide users with stronger location privacy protection and will not reduce the quality of service. We also propose a reward mechanism to encourage user participation. Finally, we implement our approach in the Remix blockchain to show the efficiency, which further indicates the potential application prospect for the distributed network environment.

The Protection of User Preference Privacy in Personalized Information Retrieval: Challenges and Overviews

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zongda Wu ◽  
Chenglang Lu ◽  
Youlin Zhao ◽  
Jian Xie ◽  
Dongdong Zou ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Privacy Protection ◽  
User Preference ◽  
User Privacy ◽  
Server Side ◽  
Algorithm Efficiency ◽  
Important Study ◽  
Basic Reference ◽  
Complete Set ◽  
Technical Features

Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.

A dummy-based user privacy protection approach for text information retrieval

2020 ◽  
Vol 195 ◽  
pp. 105679
Author(s):  
Zongda Wu ◽  
Shigen Shen ◽  
Xinze Lian ◽  
Xinning Su ◽  
Enhong Chen
Keyword(s):  
Information Retrieval ◽  
Privacy Protection ◽  
User Privacy ◽  
Text Information ◽  
Text Information Retrieval
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