Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks

Anand CHINCHORE; Frank JIANG; Guandong XU

doi:10.1007/978-3-319-21009-4_45

Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks

Anand CHINCHORE
, Frank JIANG
, Guandong XU

Offices of the President (P)

Research output: Chapter in Book/Report/Conference proceeding › Chapters

9 Citations (Scopus)

Abstract

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. Copyright © 2015 Springer International Publishing Switzerland.

Original language	English
Title of host publication	Knowledge management in organizations: 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, proceedings
Editors	Lorna UDEN, Marjan HERIČKO, I-Hsien TING
Place of Publication	Cham
Publisher	Springer
Pages	602-617
ISBN (Electronic)	9783319210094
ISBN (Print)	9783319210087
DOIs	https://doi.org/10.1007/978-3-319-21009-4_45
Publication status	Published - 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Sybil attack
Mobile social network
Anomaly detection

Access to Document

10.1007/978-3-319-21009-4_45

Other files and links

Link to publication in Scopus

CHINCHORE, A., JIANG, F., & XU, G. (2015). Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks. In L. UDEN, M. HERIČKO, & I.-H. TING (Eds.), Knowledge management in organizations: 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, proceedings (pp. 602-617). Springer. https://doi.org/10.1007/978-3-319-21009-4_45

Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks. / CHINCHORE, Anand; JIANG, Frank; XU, Guandong.
Knowledge management in organizations: 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, proceedings. ed. / Lorna UDEN; Marjan HERIČKO; I-Hsien TING. Cham: Springer, 2015. p. 602-617.

Research output: Chapter in Book/Report/Conference proceeding › Chapters

CHINCHORE, A, JIANG, F & XU, G 2015, Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks. in L UDEN, M HERIČKO & I-H TING (eds), Knowledge management in organizations: 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, proceedings. Springer, Cham, pp. 602-617. https://doi.org/10.1007/978-3-319-21009-4_45

CHINCHORE A, JIANG F, XU G. Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks. In UDEN L, HERIČKO M, TING IH, editors, Knowledge management in organizations: 10th International Conference, KMO 2015, Maribor, Slovenia, August 24-28, 2015, proceedings. Cham: Springer. 2015. p. 602-617 Epub 2015 Jan. doi: 10.1007/978-3-319-21009-4_45

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Intelligent Sybil attack detection on abnormal connectivity behavior in mobile social networks

Abstract

UN SDGs

Keywords

Access to Document

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