International Conference on Knowledge Management in Organizations

KMO 2015: Knowledge Management in Organizations pp 602-617 | Cite as

Intelligent Sybil Attack Detection on Abnormal Connectivity Behavior in Mobile Social Networks

Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 224)


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.


Sybil attack Mobile social network Anomaly detection 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Advanced Analytics InstituteUniversity of Technology SydneyUltimoAustralia

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