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Home / programming language / Online Matlab Projects / Anonymization of centralized and distributed social network by sequential clustering
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  • Lightweight Privacy-Preserving and Secure Communication Protocol for Hybrid Ad Hoc Wireless Networks

Anonymization of centralized and distributed social network by sequential clustering

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SKU: PROJ1756 Categories: Parallel and Distributed Projects, Final Year Projects, 2013 Projects, 2014 Projects, Online Matlab Projects Tags: academic projects, Android project 2013-2014, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project Abstract, dotnet project list, Final Year Projects, ieee abstracts, ieee paper download, ieee projects 2013, ieee projects 2013 paper list, ieee projects 2013-2014, ieee projects 2014, ieee projects 2014 paper list, ieee projects 2015, ieee projects 2015 paper list., ieee titles, java project list, java projects 2013-2014, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project Abstract, Vlsi project list
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Anonymization of centralized and distributed social network by sequential clustering. We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about links between nodes that are controlled by other data holders. To that end, we start with the centralized setting and offer two variants of an anonymization algorithm which is based on sequential clustering (Sq). Our algorithms significantly outperform the < Final Year Projects > SaNGreeA algorithm due to Campan and Truta which is the leading algorithm for achieving anonymity in networks by means of clustering. We then devise secure distributed versions of our algorithms. To the best of our knowledge, this is the first study of privacy preservation in distributed social networks. We conclude by outlining future research proposals in that direction.

Abstract— Anonymization of centralized and distributed social network by sequential clustering.

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