The location privacy protection research in location-based service

Zhang, Wenyan; Cui, Ximing; Li, Dengfeng; Yuan, Debao; Mengru, Wang

doi:10.1109/geoinformatics.2010.5568118

Cited by 18 publications

(8 citation statements)

References 12 publications

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“…They have revolutionized navigation (on land, in the air and at sea) and intelligent transportation system by increasing their safety and efficiency. However, user location privacy security poses a potentially grave threat [1]. In fact, it is possible to access user location information anytime and anywhere.…”

Section: Location Based Servicesmentioning

confidence: 99%

“…The large diversification of existing wireless Radio Access Technologies (RAT) and the increasing number of wirelessenabled devices are promoting the extensive application of Location Based Services (LBS) [1]. Position-dependant services include: emergency services such as rescue response [2] and security alerts, entertainment services like mobile gaming [3], medical applications [4] and a wide variety of other applications.…”

Section: Introductionmentioning

confidence: 99%

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A survey of positioning techniques and location based services in wireless networks

Yassin

Rachid

2015

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)

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Section: Location Based Servicesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A survey of positioning techniques and location based services in wireless networks

Yassin

Rachid

2015

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)

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“…These works aim to ensure that users could enjoy the location service and make attackers unable to obtain accurate position information. The main methods include K-anonymous methods, differential privacy protection methods, path obfuscation and random encryption [ 9 ]. As a traditional method, the K-anonymity method uses a position set to replace the user position, and the set contains the real user position and other fake K-1 positions.…”

Section: Related Workmentioning

confidence: 99%

A Strategy toward Collaborative Filter Recommended Location Service for Privacy Protection

Wang

Yang

Zhang

2018

Sensors

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A new collaborative filtered recommendation strategy was proposed for existing privacy and security issues in location services. In this strategy, every user establishes his/her own position profiles according to their daily position data, which is preprocessed using a density clustering method. Then, density prioritization was used to choose similar user groups as service request responders and the neighboring users in the chosen groups recommended appropriate location services using a collaborative filter recommendation algorithm. The two filter algorithms based on position profile similarity and position point similarity measures were designed in the recommendation, respectively. At the same time, the homomorphic encryption method was used to transfer location data for effective protection of privacy and security. A real location dataset was applied to test the proposed strategy and the results showed that the strategy provides better location service and protects users’ privacy.

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“…For example, a discussion of research regarding location privacy in LBSs and a method to keep the user's location private can be found in [13] and [14], respectively. To perform a service, the user must send his or her current location (obtained by using a GPS locator, for instance) to a service provider, which processes the request and then sends back an appropriate result, satisfying the given location.…”

Section: Overview Of Security and Privacy In C-lbsmentioning

confidence: 99%

Preserving User Anonymity in Context-Aware Location-Based Services: A Proposed Framework

Teerakanok¹

2013

ETRI J

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Protecting privacy is an important goal in designing location-based services. Service providers want to verify legitimate users and allow permitted users to enjoy their services. Users, however, want to preserve their privacy and prevent tracking. In this paper, a new framework providing users with more privacy and anonymity in both the authentication process and the querying process is proposed. Unlike the designs proposed in previous works, our framework benefits from a combination of three important techniques: k-anonymity, timed fuzzy logic, and a one-way hash function. Modifying and adapting these existing schemes provides us with a simpler, less complex, yet more mature solution. During authentication, the oneway hash function provides users with more privacy by using fingerprints of users' identities. To provide anonymous authentication, the concept of confidence level is adopted with timed fuzzy logic. Regarding location privacy, spatial k-anonymity prevents the users' locations from being tracked. The experiment results and analysis show that our framework can strengthen the protection of anonymity and privacy of users by incurring a minimal implementation cost and can improve functionality.

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The location privacy protection research in location-based service

Cited by 18 publications

References 12 publications

A survey of positioning techniques and location based services in wireless networks

A survey of positioning techniques and location based services in wireless networks

A Strategy toward Collaborative Filter Recommended Location Service for Privacy Protection

Preserving User Anonymity in Context-Aware Location-Based Services: A Proposed Framework

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