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Privacy threat analysis of mobile social network data publishing
conference contribution
posted on 2018-01-01, 00:00 authored by Jemal AbawajyJemal Abawajy, M I H Ninggal, Z A Aghbari, A B Darem, A AlhashmiWith mobile phones becoming integral part of modern life, the popularity of mobile social networking has tremendously increased over the past few years, bringing with it many benefits but also new trepidations. In particular, privacy issues in mobile social networking has recently become a significant concern. In this paper we present our study on the privacy vulnerability of the mobile social network data publication with emphases on a re-identification and disclosure attacks. We present a new technique for uniquely identifying a targeted individual in the anonymized social network graph and empirically demonstrate the capability of the proposed approach using a very large social network datasets. The results show that the proposed approach can uniquely re-identify a target on anonymized social network data with high success rate.
History
Event
European Alliance for Innovation. Conference (13th : 2017 : Niagara Falls, Ont.)Volume
239Series
European Alliance for Innovation ConferencePagination
60 - 68Publisher
SpringerLocation
Niagara Falls, Ont.Place of publication
Cham, SwitzerlandPublisher DOI
Start date
2017-10-22End date
2017-10-25ISSN
1867-8211ISBN-13
9783319788159Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications EngineeringEditor/Contributor(s)
X Lin, A Ghorbani, K Ren, S Zhu, A ZhangTitle of proceedings
SecureComm 2017: Proceedings of the 13th International Conference on Security and Privacy in Communication NetworksUsage metrics
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