Where Are You Bob? Privacy-Preserving Proximity Testing with a Napping Party

Oleynikov, Ivan; Pagnin, Elena; Sabelfeld, Andrei

doi:10.1007/978-3-030-58951-6_33

Cited by 5 publications

(3 citation statements)

References 34 publications

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“…Yi et al [1] and Guan et al [2] focused on privacy-preserving k-nearest neighbor queries schemes where a user can query the server for closest point of interest (POI) and the server cannot identify the user's location. Hallgren et al [5] and Oleynikov et al [6] studied privacy-preserving location proximity testing problem. Both used partially homomorphic encryption to achieve an exact computation of location proximity with protecting the location and distance.…”

Section: Introductionmentioning

confidence: 99%

“…In [5], principals made sure whether they were within a certain distance from each other without revealing any further information. Oleynikov et al [6] proposed a novel privacypreserving proximity testing protocol such that one party could * The corresponding author. perform offline testing, which break the limitation where the parties must be online and interact directly with each other.…”

Section: Introductionmentioning

confidence: 99%

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Privacy-Preserving Closest Point Determination Based on Ciphertext Comparison

et al. 2022

2022 IEEE International Performance, Computing, and Communications Conference (IPCCC)

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Closest point determination is a fundamental problem that arises in location-based services. In this paper, we study privacy-preserving closest point determination problem involving at least three parties, which focuses on determining the closest point without revealing location information. First, we present a three-party integer comparison protocol using homomorphic encryption systems in order to achieve the ciphertext comparison. Second, we propose a three-party and a multi-party protocol based on the integer comparison protocol to determine the closest point and prove that they are secure against semi-honest adversaries in the standard model. The proposed protocols are built on partially homomorphic encryption systems and can keep location and distance confidential. Finally, we confirm that our protocols reach a better balance between complexity and security. And experimental results demonstrate that our protocol is feasible and effective.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Privacy-Preserving Closest Point Determination Based on Ciphertext Comparison

et al. 2022

2022 IEEE International Performance, Computing, and Communications Conference (IPCCC)

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“…Moreover, the problem of Private Proximity Testing (PPT) is a similar issue, which is only applicable in smart devices. It has attracted the attention of some researchers since 2006 [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. In PPT, the proximity of two Location Based Services (LBS) are securely examined.…”

Section: Introductionmentioning

confidence: 99%

Private Trajectory Intersection Testing: Is Garbled Circuit Better than Custom Protocols?

Dehghan

Sadeghiyan

Khosravian

2021

IJE

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In this paper, two protocols are presented for private intersection detection of two moving objects' trajectories. To design the first protocol, we simplify the problem of finding the intersection points to the problem of finding the common roots of the polynomials, which represent the moving objects' trajectories. Thereafter, GrÖbner Basis is used to design a novel secure protocol to find the common roots of the polynomials. Another protocol is also designed based on the distance computation of two trajectories' curves. The complexity of the GrÖbner-based protocol for finding the common roots of polynomials is numerical. Its complexity is much lower than the complexity of the garbled circuitbased protocol for Euclidean Distance Computation of l points and the complexity of the protocols for private proximity testing.

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