Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/26275
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dc.contributor.authorAlharbi, Hanien_UK
dc.contributor.authorAloufi, Khaliden_UK
dc.contributor.authorHussain, Amiren_UK
dc.contributor.editorLiu, C-Len_UK
dc.contributor.editorHussain, Aen_UK
dc.contributor.editorLuo, Ben_UK
dc.contributor.editorTan, KCen_UK
dc.contributor.editorZeng, Yen_UK
dc.contributor.editorZhang, Zen_UK
dc.date.accessioned2017-12-02T00:12:22Z-
dc.date.available2017-12-02T00:12:22Z-
dc.date.issued2016en_UK
dc.identifier.urihttp://hdl.handle.net/1893/26275-
dc.description.abstractMillions of users world-wide are sharing content using the Peer-to-Peer (P2P) client network. While new innovations bring benefits, there are nevertheless some dangers associated with them. One of the main threats is P2P worms that can penetrate the network even from a single node and can then spread very quickly. Many attempts have been made in this domain to model the worm propagation behaviour, and yet no single model exists that can realistically model the process. Most researchers have considered disease epidemic models for modelling the worm propagation process. Such models are, however, based on strong assumptions which may not necessarily be valid in real-world scenarios. In this paper, a new biologically-inspired analytical model is proposed, one that considers configuration diversity, infection time lag, user-behaviour and node mobility as the important parameters that affect the worm propagation process. The model is flexible and can represent a network where all nodes are mobile or a heterogeneous network, where some nodes are static and others are mobile. A complete derivation of each of the factors is provided in the analytical model, and the results are benchmarked against recently reported analytical models. A comparative analysis of simulation results indeed shows that our proposed biologically-inspired model represents a more realistic picture of the worm propagation process, compared to the existing state-of-the-art analytical models.en_UK
dc.language.isoenen_UK
dc.publisherSpringeren_UK
dc.relationAlharbi H, Aloufi K & Hussain A (2016) A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks. In: Liu C, Hussain A, Luo B, Tan K, Zeng Y & Zhang Z (eds.) Advances in Brain Inspired Cognitive Systems: 8th International Conference, BICS 2016, Beijing, China, November 28-30, 2016, Proceedings. Lecture Notes in Computer Science, 10023. BICS 2016: Advances in Brain Inspired Cognitive Systems 8th International Conference, Beijing, China, 28.11.2016-30.11.2016. Cham, Switzerland: Springer, pp. 251-263. https://doi.org/10.1007/978-3-319-49685-6_23en_UK
dc.relation.ispartofseriesLecture Notes in Computer Science, 10023en_UK
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.titleA new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networksen_UK
dc.typeConference Paperen_UK
dc.rights.embargodate3000-10-14en_UK
dc.rights.embargoreason[alharbi_etal_LNCS_2016.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.identifier.doi10.1007/978-3-319-49685-6_23en_UK
dc.citation.issn0302-9743en_UK
dc.citation.spage251en_UK
dc.citation.epage263en_UK
dc.citation.publicationstatusPublisheden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.author.emailahu@cs.stir.ac.uken_UK
dc.citation.btitleAdvances in Brain Inspired Cognitive Systems: 8th International Conference, BICS 2016, Beijing, China, November 28-30, 2016, Proceedingsen_UK
dc.citation.conferencedates2016-11-28 - 2016-11-30en_UK
dc.citation.conferencelocationBeijing, Chinaen_UK
dc.citation.conferencenameBICS 2016: Advances in Brain Inspired Cognitive Systems 8th International Conferenceen_UK
dc.citation.date13/11/2016en_UK
dc.citation.isbn978-3-319-49684-9en_UK
dc.citation.isbn978-3-319-49685-6en_UK
dc.publisher.addressCham, Switzerlanden_UK
dc.contributor.affiliationUniversity of Stirlingen_UK
dc.contributor.affiliationTaibah Universityen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.scopusid2-s2.0-84997386094en_UK
dc.identifier.wtid538789en_UK
dc.contributor.orcid0000-0002-8080-082Xen_UK
dc.date.accepted2016-08-10en_UK
dc.date.filedepositdate2017-12-01en_UK
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings

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