Graduate School and Research Center in Digital Sciences

Privacy preserving similarity detection for data analysis

Leontiadis, Iraklis; Önen, Melek; Molva, Refik; Chorley, M.J; Colombo, G.B

CSAR 2013, Collective Social Awareness and Relevance Workshop, co-located with the 3rd international conference on Social Computing and its Applications, 30 September-2 October 2013, Karlsruhe, Germany

Current applications tend to use personal sensitive information to achieve better quality with respect to their services. Since the third parties are not trusted the data must be protected such that individual data privacy is not compromised but at the same time operations on it would be compatible. A wide range of data analysis operations entails a similarity detection algorithm between user data. For instance clustering on big data groups together objects based on the heuristic that similar objects are likely to be put under the same cluster. Similarity decisions are important for numerous applications such as: online social networks, recommendations systems and behavioral advertisement. In this paper we propose a mechanism that protects user privacy and preserves data similarity results although encrypted. We analyze the security of the scheme and we further demonstrate its correctness and feasibility through a real life experiment where "personality traits" by users are collected for a 4square application.

Document Doi Hal Bibtex

Title:Privacy preserving similarity detection for data analysis
Keywords:Information security, privacy, data analysis, similarity detection
Department:Digital Security
Eurecom ref:4096
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Bibtex: @inproceedings{EURECOM+4096, doi = {}, year = {2013}, title = {{P}rivacy preserving similarity detection for data analysis}, author = {{L}eontiadis, {I}raklis and {\"{O}}nen, {M}elek and {M}olva, {R}efik and {C}horley, {M}.{J} and {C}olombo, {G}.{B}}, booktitle = {{CSAR} 2013, {C}ollective {S}ocial {A}wareness and {R}elevance {W}orkshop, co-located with the 3rd international conference on {S}ocial {C}omputing and its {A}pplications, 30 {S}eptember-2 {O}ctober 2013, {K}arlsruhe, {G}ermany}, address = {{K}arlsruhe, {GERMANY}}, month = {09}, url = {} }
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