Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/8233
Title: Identifying Provenance of Information and Anomalous Paths in Attributed Social Networks
Authors: Trivedi, H.
Bindu, P.V.
Santhi Thilagam, P.
Issue Date: 2018
Citation: Proceedings of the 2nd International Conference on Computing Methodologies and Communication, ICCMC 2018, 2018, Vol., , pp.914-919
Abstract: Information 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.
URI: https://idr.nitk.ac.in/jspui/handle/123456789/8233
Appears in Collections:2. Conference Papers

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