Fog-Assisted Privacy Preservation Scheme for Location-Based Services Based on Trust Relationship
01 Oct 2020-Vol. 12, Iss: 4, pp 48-62
TL;DR: The experimental results show that the proposed FPriLBS outperforms the existing schemes in terms of processing time and processing cost.
Abstract: With advancements in smart mobile devices and their capabilities, location-based services have gained utmost importance, as its individual and social benefits are enormous. Users of location-based services have a concern to the security issues posed by its usage as the location service providers track the users' interests, behavior, and identity information. Most of the location-based services are launched from mobile phones that have stringent resources; hence incorporating encryption schemes becomes tedious, and further, dual identity attacks uncover the encrypted message. A fog-assisted privacy protection scheme for location-based service (FPriLBS) employs a semi-trusted third party as a fog server to eliminate redundant queries submitted to the location service provider in addition to the trusted helper selection scheme which hides the real identity of the user from the fog server. The experimental results show that the proposed FPriLBS outperforms the existing schemes in terms of processing time and processing cost.
Citations
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01 Jan 2021
TL;DR: This manuscript focuses on grid computing platform that exposes to two types of threats: crash and silent data corruption faults, which cause the application's failure and uses Weibull distribution to express these random faults to create the optimal time to save checkpoints.
Abstract: With the increase in high-performance computing platform size, it makes the system reliability more challenging, and system mean time between failures (MTBF) may be too short to supply a total fault-free run. Thereby, to achieve greater benefit from these systems, the applications must include fault tolerance mechanisms to satisfy the required reliability. This manuscript focuses on grid computing platform that exposes to two types of threats: crash and silent data corruption faults, which cause the application's failure. This manuscript also addresses the problem of modeling resource availability and aims to minimize the overhead of checkpoint/recovery-fault tolerance techniques. Modeling resources faults has commonly been addressed with exponential distribution, but that isn't fully realistic for the transient errors, which appear randomly. In the manuscript, the authors use Weibull distribution to express these random faults to create the optimal time to save checkpoints.
TL;DR: This paper proposes a security-enhanced query result verification scheme (SEQRVS) for the outsourced data in a LBS, and designs a novel storage structure to enhance the ability of privacy preservation for the Outsourced data.
Abstract: Location-based services (LBSs) facilitate people’s lives; location-based service providers (LBSPs) usually outsource services to third parties to provide better services. However, the third party is a dishonest entity that might return incorrect or incomplete query results under the consideration of saving storage space and computation resources. In this paper, we propose a security-enhanced query result verification scheme (SEQRVS) for the outsourced data in a LBS. Specifically, while retaining fine-grained query result verification, we improve the construction process of verification objects to enhance the security of the outsourced data. To prevent the third party from deducing the knowledge of the outsourced data stored in itself (statistically), our scheme designs a novel storage structure to enhance the ability of privacy preservation for the outsourced data. Furthermore, based on the secure keyword search and query result verification mode proposed in our scheme, the user cannot only verify the correctness and completeness of the query result but also achieve consistency verification by the blockchain. Finally, the security analysis and extensive simulation results show the security and practicality of the proposed scheme.
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149 citations
08 Jul 2014
TL;DR: The proposed FINE framework employs a ciphertext-policy anonymous attribute-based encryption technique to achieve fine-grained access control, location privacy, confidentiality of the LBS data and its access policy, and accurate LBS query result while without involving any trusted third party.
Abstract: In this paper, we propose a fine-grained privacy- preserving location-based service (LBS) framework, called FINE, for mobile devices. It adopts the data-as-a-service (DaaS) model, where the LBS provider publishes its data to a third party (e.g., cloud server) who executes users' LBS queries. The pro- posed FINE framework employs a ciphertext-policy anonymous attribute-based encryption technique to achieve fine-grained access control, location privacy, confidentiality of the LBS data and its access policy, and accurate LBS query result while without involving any trusted third party. Moreover, the proposed FINE framework also integrates the transformation key and proxy re- encryption to migrate most of computation-intensive tasks from the LBS provider and users to the cloud server. This property keeps mobile devices away from massive resource-consuming operations. Extensive analysis shows that our proposed FINE framework is secure and highly efficient for mobile devices in terms of computation and communication cost.
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TL;DR: A coalitional game theoretic framework is developed to devise social-tie based cooperation strategies for device-to-device communications and a network assisted relay selection mechanism is developed that can achieve up-to 122% performance gain over the case without D2D cooperation.
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115 citations
TL;DR: This article introduces an innovative framework, called KCE, to dynamically detect network structure and manage communication resources, leveraging the insightful knowledge obtained from D2D communications among mobile users.
Abstract: MEC has been gaining great interest in addressing the limited computational capability in 5G mobile networks. Although there are several existing works about MEC, for example, utilizing WNV and SDN, virtualized D2D communication together with learning-based D2D communication systems, such as social and smart D2D networking systems, have not been investigated by researchers, while knowledge of the edge is lacking. In this article, we introduce an innovative framework, called KCE, to dynamically detect network structure and manage communication resources, leveraging the insightful knowledge obtained from D2D communications among mobile users. Further, to support trustworthy network access and to meet different QoS requirements in the proposed architecture, specific SPs are selected from InPs by a KCE server. As such, the chosen SPs' resources can be dynamically allocated to meet various service requirements by virtualized D2D communication techniques. Simulation results demonstrate the effectiveness of the proposed framework under different scenarios and parameter settings.
95 citations