Spatiotemporal Access Control Enforcement under Uncertain Location Estimates

Abstract

Abstract. In a mobile environment, user's physical location plays an important role in determining access to resources. However, because current moving object databases do not keep the exact location of the moving objects, but rather maintain their approximate location for reasons of minimizing the updates, the access request evaluation cannot always guarantee the intended access control policy requirements. This may be risky to the system's security, especially for the highly sensitive resources. In this paper, we introduce an authorization model that takes the uncertainty of location measures into consideration for specifying and evaluating access control policies. An access request is granted only if the confidence level of the location predicate exceeds the predefined uncertainty threshold level specified in the policy. However, this access request evaluation is computationally expensive as it requires to evaluate a location predicate condition and may also require evaluating the entire moving object database. For reducing the cost of evaluation, in this paper, we compute lower and upper bounds (Rmin and Rmax) on the region that minimize the region to be evaluated thereby allowing unneeded moving objects to be discarded from evaluation. We show how Rmin and Rmax can be computed and maintained, and provide algorithms to process access requests.

Efficient Evaluation of Location Predicates for Access Control Systems

“…Shin et al proposed a special probabilistic filter for evaluating location predicates in LBAC systems even for positioning systems that return an uncertainty area wherein the position is modeled as a Gaussian distribution [3]. The filter reduces the overall amount of exact location predicate evaluations by computing boundaries for a given location predicate on a rectangular logical location and a set of uncertain user and object locations.…”

“…Hence, H Shin. et al proposed to model user locations as circular uncertainty areas (UA) along with a probability density function (pdf) [3]. This leads to the problem that the evaluation of location predicates depends on a very computationally demanding numerical integration of the underlying pdf.…”

Enabling secure location-based services in mobile cloud computing

“…Furthermore, since interval or range predicates are introduced into our location-based access control mechanism, it 2 The anonymity set is defined as the group of people who hold the same access privileges. allows a user to use a coarse-grained spatio-temporal information in location to achieve obfuscation.…”

“…The increasing popularity of LBSs has led to a renewed research interest in location-based security, where one important problem is to enforce fine-grained spatio-temporal access control on a large number of users to prevent the unauthorized access of services and the disclosure of valuable LBS data [2,3]. Moreover, the possibility to identify the user who requests a given service and her/his location information at the time of the request has raised much concern on potential privacy violation [4].…”

Cryptographic Spatio-temporal Predicates for Location-Based Services

“…The increasing popularity of LBSs has led to a renewed research interest in location-based security, where one important problem is to enforce fine-grained spatiotemporal access control on a large number of users to prevent the unauthorized access of services and the disclosure of valuable LBS data [2], [3], [4], [5]. Moreover, the possibility to identify the user who requests a given service and her/his 1 https://foursquare.com; https://www.loopt.com; http://maps.google.com location information at the time of the request has raised much concern on potential privacy violation [6], [7], [8], [9].…”