Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/8233
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dc.contributor.authorTrivedi, H.-
dc.contributor.authorBindu, P.V.-
dc.contributor.authorSanthi Thilagam, P.-
dc.date.accessioned2020-03-30T10:18:15Z-
dc.date.available2020-03-30T10:18:15Z-
dc.date.issued2018-
dc.identifier.citationProceedings of the 2nd International Conference on Computing Methodologies and Communication, ICCMC 2018, 2018, Vol., , pp.914-919en_US
dc.identifier.urihttps://idr.nitk.ac.in/jspui/handle/123456789/8233-
dc.description.abstractInformation provenance problem is an important and challenging problem in social network analysis and it deals with identifying the origin or source of information spread in a social network. In this paper, an approach for detecting the source of an information spread as well as suspicious anomalous paths in a social network is proposed. An anomalous path is a sequence of nodes that propagates an anomalous information to the given destination nodes who cause an anomalous event. The proposed approach is based on attribute-based anomalies and information cascading technique. The anomalous paths are identified in two steps. The first step assigns an anomalous score to each and every vertex in the given graph based on suspicious attributes. The second step detects the source and suspicious anomalous paths in the network using the anomaly scores. The approach is tested on datasets such as Enron and Facebook to demonstrate its effectiveness. Detecting anomalous paths is useful in several applications including identifying terrorist attacks communication path, disease spreading pattern, and match-fixing hidden path between bookie and a cricketer. � 2018 IEEE.en_US
dc.titleIdentifying Provenance of Information and Anomalous Paths in Attributed Social Networksen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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