Spatio-Temporal Attestation for Location-based Services Using Private Signatures
Project Team: Prof. XU, Jian Liang |
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Abstract: |
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In location-based services, there has been a growing necessity against location cheating and for location trustworthiness. In this project, we propose "spatio-temporal attestation", where a mobile user testifies or attests to a service provider the genuineness of his/her input location against some spatio-temporal predicate, such as "being in a specific region during a time period". The major challenge is the need of protecting location privacy of mobile users against the service provider during the attestation process.
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System Model: |
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The system model consists of three parties (shown in the figure above): (i) the mobile user who generates location points continuously; (ii) the authentication server who signs locations; and (iii) the location-based service provider (SP) which needs the user to attest to the predicate and (if verified) proceeds with the service. The system works in two phases: the signing phase that generates the signatures and the attestation phase that uses them to attest to predicates.
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Problems and Methodology: |
- Range-based Spatial Predicate
The problem is for the user to attest to the SP in each dimension of predicate R and without disclosing p, such that R.l ≤ p ≤ R.u, where l and u denote the lower and upper bounds of R, respectively. The solution is the design of a “magic” function g(), which only accepts non-negative numbers and it follows g(x) = g(x - a) ◦ g(a), where ◦ is a well-defined operation.
- Distance-based Spatial Predicate
The problem is for the user to attest to the SP that p is within σ distance away from a subject point s. The “close-to” predicate is a special case of this problem with a small σ. In this project, we focus on two popular distance metrics in location-based services, namely the Manhattan and the Euclidean distances.
- Continuous Spatio-Temporal Trajectories
we assume the trajectory consists of a series of spatial points in ascending timestamps. Formally, T(p) = { (pt0, t0), (pt1, t1),…, (ptn, tn) }. Applying the previous schemes for spatial predicates is inefficient for this problem, so we propose various indexing schemes, such as a binary search tree or carry heaps, to pre-aggregate adjacent timestamps.
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For further information on this project, please contact Prof. XU, Jian Liang.
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