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Home / programming language / Online Java Projects / FaceChange: Attaining Neighbor Node Anonymity in Mobile Opportunistic Social Networks with Fine-grained Control
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FaceChange: Attaining Neighbor Node Anonymity in Mobile Opportunistic Social Networks with Fine-grained Control

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SKU: PROJ8411 Categories: 2018-2019 Projects, Networking Projects, Online Java Projects 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, Matlab Project, PHP Project, Students Projects
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FaceChange: Attaining Neighbor Node Anonymity in Mobile
Opportunistic Social Networks with Fine-grained Control

Abstract-In mobile opportunistic social networks (MOSNs),mobile devices carried by people communicate with each other directly when they meet for proximity-based MOSN services (e.g., file sharing) without the support of infrastructures. In current methods, when nodes meet, they simply communicate with their real IDs, which leads to privacy and security concerns. Anonymizing real IDs among neighbor nodes solves such concerns. However, this prevents nodes from collecting real ID based encountering information, which is needed to support MOSN services. Therefore, in this paper, we propose FaceChange that can support both anonymizing real IDs among neighbor nodes and collecting real ID based encountering information. For node anonymity, two encountering nodes communicate anonymously.Only when the two nodes disconnect with each other, each node forwards an encrypted encountering evidence to the encountered node to enable encountering information collection. A set of novel schemes are designed to ensure the confidentiality and uniqueness of encountering evidences. FaceChange also supports fine-grained control over what information is shared with the encountered node based on attribute similarity (i.e., trust), which is calculated without disclosing attributes. Advanced extensions for sharing real IDs between mutually trusted nodes and more efficient encountering evidence collection are also proposed. Extensive analysis and experiments show the effectiveness of FaceChange on protecting node privacy and meanwhile supporting the encountering information collection in MOSNs. Implementation on smartphones also demonstrates its energy efficiency.

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