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Home / programming language / Online Dotnet Projects / STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users
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STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

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SKU: PROJ7097 Categories: 2017 Projects, Final Year Projects, Networking Projects, Online Dotnet Projects, programming language Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

Abstract— Location-based services are quickly becoming immensely popular. In addition to services based on users’ current location, many potential services rely on users’ location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, it can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non-transferability of the location proofs and protects users’ privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light-weight entropy-based trust evaluation approach. Our prototype implementation on the Android plat-form shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy-based trust model is able to achieve high (>0:9) collusion detection accuracy. As location-enabled mobile devices proliferate, location-based services are rapidly becoming immensely popular. Most of the current location-based services for mobile devices are based on users’ current location. Users discover their locations and share them with a server. < final year projects >

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