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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

224

Pagination

602-617

Location

Maribor, Slovenia

Start date

2015-08-24

End date

2015-08-28

ISSN

1865-1348

ISBN-13

9783319210094

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

Uden L, Heričko M, Ting IH

Title of proceedings

KMO 2015 : Knowledge management in organizations : 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, Proceedings

Event

Knowledge Management in Organizations. Conference (2015 : 10th : Maribor, Slovenia)

Publisher

Springer

Place of publication

Berlin, Germany

Series

Lecture Notes in Business Information Processing

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