Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks
conference contribution
posted on 2015-01-01, 00:00 authored by A Chinchore, Frank JiangFrank Jiang, G Xu© Springer International Publishing Switzerland 2015. There have been a large number of researches on mobile networks in the literature, focusing on a variety of secured applications over the network, including the use of their connections, fake identification and attacks on social group. These applications are created for the intention to collect confidential information, money laundering, blackmailing and to perform other crime activity. The purpose of this research is to identify the behavior of the honest node (network account) and fake node (network account) on mobile social network. In this research, the behavior survey of these nodes is carried out and further analysed with the help of graph-based Sybil detection system. This paper particularly studies Sybil attacks and its defense system for IoT (Internet-of-Things) environment. To be implied, the identification of each forged Sybil node is to be tracked on the basis of nodes connectivity and their timing of connectivity as well as frequency among each other. Sybil node has a forged identity in different locations and also reports its virtual location information to servers.
History
Volume
224Pagination
602-617Location
Maribor, SloveniaPublisher DOI
Start date
2015-08-24End date
2015-08-28ISSN
1865-1348ISBN-13
9783319210094Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
Uden L, Heričko M, Ting IHTitle of proceedings
KMO 2015 : Knowledge management in organizations : 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, ProceedingsEvent
Knowledge Management in Organizations. Conference (2015 : 10th : Maribor, Slovenia)Publisher
SpringerPlace of publication
Berlin, GermanySeries
Lecture Notes in Business Information ProcessingUsage metrics
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