Trustworthy knowledge diffusion model based on risk discovery on peer-to-peer networks
- Authors
- Jung, Jason J.
- Issue Date
- Apr-2009
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Risk discovery; Knowledge dissemination; Distributed knowledge management; Social network analysis
- Citation
- EXPERT SYSTEMS WITH APPLICATIONS, v.36, no.3, pp 7123 - 7128
- Pages
- 6
- Journal Title
- EXPERT SYSTEMS WITH APPLICATIONS
- Volume
- 36
- Number
- 3
- Start Page
- 7123
- End Page
- 7128
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/37770
- DOI
- 10.1016/j.eswa.2008.08.048
- ISSN
- 0957-4174
1873-6793
- Abstract
- Knowledge management systems have been inter-networked with each other on distributed environment, e.g., peer-to-peer (P2P) networks. However, as some of users take malicious actions, the corresponding information (or knowledge) on the P2P networks might be contaminated and distorted. In this paper, we propose a robust information diffusion (or propagation) model to detect the malicious peers from which the risks (e.g., information distortion) was originated on P2P networks. Thereby, we want to trace social interactions among peers to identify a recommendation flow and collect them. Given a set of recommendation flows, statistical sequence mining method is exploited to discover a certain social position which provides peculiar patterns on the P2P networks. For evaluating the proposed method, we conducted two experimentations with NetLogo simulation platform for risk discovery on social network. (C) 2008 Elsevier Ltd. All rights reserved.
- Files in This Item
-
- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.