|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Title:||A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks|
|Citation:||Alharbi H, Aloufi K & Hussain A (2016) A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks In: Liu C-L, Hussain A, Luo B, Tan KC, Zeng Y, Zhang Z (ed.) Advances in Brain Inspired Cognitive Systems: 8th International Conference, BICS 2016, Beijing, China, November 28-30, 2016, Proceedings, Cham, Switzerland: Springer. BICS 2016: Advances in Brain Inspired Cognitive Systems 8th International Conference, 28.11.2016 - 30.11.2016, Beijing, China, pp. 251-263.|
|Series/Report no.:||Lecture Notes in Computer Science, 10023|
|Conference Name:||BICS 2016: Advances in Brain Inspired Cognitive Systems 8th International Conference|
|Conference Location:||Beijing, China|
|Abstract:||Millions 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.|
|Status:||Book Chapter: publisher version|
|Rights:||The 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.|
|alharbi_etal_LNCS_2016.pdf||2.6 MB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.