A novel attack to spatial cloaking schemes in location-based services

Niu, Ben; Zhu, Xiaoyan; Li, Qinghua; Chen, Jie; Li, Hui

doi:10.1016/j.future.2014.10.026

Cited by 48 publications

(50 citation statements)

References 32 publications

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“…Rebollo et al [14] further this conception in query anonymity, and utilized entropy to select the optimal submitting user [25]. Niu et al [15] proposed a Variance-Based Attack (VBA) to successfully attack the existing algorithms, then they proposed a random walk-based cloaking algorithm to remedy drawbacks of these algorithms.…”

Section: Related Workmentioning

confidence: 99%

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Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

2018

Teh. vjesn.

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Abstract:In location-based services of continuous query, it is easier than snapshot to confirm whether a location belongs to a particular user, because sole location can be composed into a trajectory by profile correlation. In order to cut off the correlation and disturb the sub-trajectory, an un-detective region called mix-zone was proposed. However, at the time of this writing, the existing algorithms of this type mainly focus on the profiles of ID, passing time, transition probability, mobility patterns as well as road characteristics. In addition, there is still no standard way of coping with attacks of correlating each location by mining out query content and time interval from the subtrajectory. To cope with such types of attack, users have to generalize their query contents and time intervals similarity. Hence, this paper first provided an attack model to simulate the adversary correlating the real location with a higher probability of query content and time interval similarity. Then a user collaboration mix-zone (CoMix) that can generalize these two types of profiles is proposed, so as to achieve location privacy. In CoMix, each user shares the common profile set to lowering the probability of success opponents to get the actual position through the correlation of location. Thirdly, entropy is utilized to measure the level of privacy preservation. At last, this paper further verifies the effectiveness and efficiency of the proposed algorithm by experimental evaluations.

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Section: Related Workmentioning

confidence: 99%

“…The aims of this paper can be described as to resist the potential correlation attack, take advantage over the collaborative user scheme [14,15] and achieve the query ldiversity [16] and time interval consistency. Based on these purposes, a user collaborative mix-zone (short for CoMix) is proposed.…”

Section: Introductionmentioning

confidence: 99%

Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

2018

Teh. vjesn.

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“…(1) Avoid VBAs [3] in the center location of the pseudoobfuscation area generated for the user's location.…”

Section: Producing the Obfuscation Areas Of Multiplementioning

confidence: 99%

“…However, the approaches proposed in those studies search for − 1 conspirators surrounding the user, which may enable attackers to triangulate a user within an obfuscation area (OA) and deploy a variance-based attack (VBA) [3]. In [3], an approach was proposed that searches for other conspirators surrounding a user. Subsequently, a random conspirator in the group is selected to search for other conspirators.…”

Section: Introductionmentioning

confidence: 99%

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Unchained Cellular Obfuscation Areas for Location Privacy in Continuous Location-Based Service Queries

Luo

Yang

2017

Wireless Communications and Mobile Computing

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To access location-based service (LBS) and query surrounding points of interest (POIs), smartphone users typically use builtin positioning functions of their phones when traveling at unfamiliar places. However, when a query is submitted, personal information may be leaked when they provide their real location. Current LBS privacy protection schemes fail to simultaneously consider real map conditions and continuous querying, and they cannot guarantee privacy protection when the obfuscation algorithm is known. To provide users with secure and effective LBSs, we developed an unchained regional privacy protection method that combines query logs and chained cellular obfuscation areas. It adopts a multiuser anonymizer architecture to prevent attackers from predicting user travel routes by using background information derived from maps (e.g., traffic speed limits). The proposed scheme is completely transparent to users when performing continuous location-based queries, and it combines the method with actual road maps to generate unchained obfuscation areas that conceal the actual locations of users. In addition to using a caching approach to enhance performance, the proposed scheme also considers popular tourist POIs to enhance the cache data hit ratio and query performance.

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Intelligent pseudo‐location recommendation for protecting personal location privacy

Huang

Deng

Xie

et al. 2019

Concurrency and Computation

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Summary Individuals' right to privacy includes control over access to their location information. With the advent of location‐based services and personal transport services (such as ridesharing), the risk of location privacy breaches is increased greatly. The potential negative effects of location privacy leakages include spam location‐based service flooding, threats to personal safety (such as physical attacks), and intrusion related to access to private places (such as homes and hospitals). Therefore, protecting the privacy of users' real locations is becoming increasingly important. This is often achieved using a pseudo‐location near the real location, but existing pseudo‐location generators, such as NRand and the uniform random method, suffer from statistical inference, which can infer the obfuscation domain to cover the real location. In this paper, we propose an intelligent pseudo‐location recommendation (IPLR) method to reduce the risk of a statistical inference attack. In IPLR, we generate a random substitute of the real location to attract the adversary and thus hide the real location. Then, the pseudo‐location is generated in the neighborhood of the random substitute location following a normal distribution; the random substitute location is changed frequently to confuse attackers. In particular, we define three levels of location privacy, ie, address level, street level, and district level, to evaluate the effectiveness of the IPLR method. Our experimental study using simulation data demonstrates that the proposed IPLR method achieves lower risk of location privacy leakage and higher probabilities of safety in all three levels of location privacy than NRand and the random method. It also demonstrates the effectiveness of the proposed IPLR to balance location privacy and service quality.

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A novel attack to spatial cloaking schemes in location-based services

Cited by 48 publications

References 32 publications

Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

Unchained Cellular Obfuscation Areas for Location Privacy in Continuous Location-Based Service Queries

Intelligent pseudo‐location recommendation for protecting personal location privacy

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