Propagation model of smartphone worms based on semi-Markov process and social relationship graph Peng,S, Wu,M, Wang,G and Yu,S 2014, Propagation model of smartphone worms based on semi-Markov process and social relationship graph, Computers and Security, vol. 44, pp. 92-103, doi: 10.1016/j.cose.2014.04.006. Attached Files Name Description MIMEType Size Downloads Title Propagation model of smartphone worms based on semi-Markov process and social relationship graph Author(s) Peng,S Wu,M Wang,G Yu,S orcid.org/0000-0003-4485-6743 Journal name Computers and Security Volume number 44 Start page 92 End page 103 Total pages 12 Publisher Elsevier Place of publication Oxon, United Kingdom Publication date 2014-07 ISSN 0167-4048 Keyword(s) Propagation model Semi-Markov process Smartphone Social relationship graph Worm Science & Technology Technology Computer Science, Information Systems Computer Science NETWORKS DYNAMICS Summary Smartphone applications are getting more and more popular and pervasive in our daily life, and are also attractive to malware writers due to their limited computing source and vulnerabilities. At the same time, we possess limited understanding of our opponents in cyberspace. In this paper, we investigate the propagation model of SMS/MMS-based worms through integrating semi-Markov process and social relationship graph. In our modeling, we use semi-Markov process to characterize state transition among mobile nodes, and hire social network theory, a missing element in many previous works, to enhance the proposed mobile malware propagation model. In order to evaluate the proposed models, we have developed a specific software, and collected a large scale real-world data for this purpose. The extensive experiments indicate that the proposed models and algorithms are effective and practical. © 2014 Elsevier Ltd. All rights reserved. Language eng DOI 10.1016/j.cose.2014.04.006 Field of Research 080502 Mobile Technologies Socio Economic Objective 890103 Mobile Data Networks and Services HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2014, Elsevier Persistent URL http://hdl.handle.net/10536/DRO/DU:30072594 Document type: Journal Article Collection: School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 22 Apr 2015, 12:22:19 EST Wed, 22 Apr 2015, 15:43:48 EST Thu, 23 Apr 2015, 05:00:38 EST Thu, 23 Apr 2015, 06:08:17 EST Thu, 23 Apr 2015, 10:27:07 EST Thu, 23 Apr 2015, 10:30:01 EST Filtered Full Citation counts:   Cited 18 times in TR Web of Science Cited 20 times in Scopus Search Google Scholar Access Statistics: 267 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Wed, 22 Apr 2015, 15:43:48 EST

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