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Xin-Li Huang, Fu-Tai Zou, Fan-Yuan Ma. Targeted Local Immunization in Scale-Free Peer-to-Peer Networks[J]. Journal of Computer Science and Technology, 2007, 22(3): 457-468.
Citation: Xin-Li Huang, Fu-Tai Zou, Fan-Yuan Ma. Targeted Local Immunization in Scale-Free Peer-to-Peer Networks[J]. Journal of Computer Science and Technology, 2007, 22(3): 457-468.

Targeted Local Immunization in Scale-Free Peer-to-Peer Networks

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  • Received Date: August 02, 2006
  • Revised Date: October 30, 2006
  • Published Date: May 14, 2007
  • The power-law node degree distributions of peer-to-peer overlay networksmake them extremely robust to random failures whereas highly vulnerableunder intentional targeted attacks. To enhance attack survivability ofthese networks, DeepCure, a novel heuristic immunizationstrategy, is proposed to conduct decentralized but targetedimmunization. Different from existing strategies, DeepCure identifiesimmunization targets as not only the highly-connected nodes but also thenodes with high {\it availability} and/or high {\it link load}, with theaim of injecting immunization information into just {\it right} targetsto cure. To better trade off the cost and the efficiency, DeepCuredeliberately select these targets from 2-{\it local} neighborhood, aswell as topologically-remote but semantically-close friends if needed.To remedy the weakness of existing strategies in case of sudden epidemicoutbreak, DeepCure is also coupled with a local-hub oriented {\it ratethrottling} mechanism to enforce proactive rate control. Extensivesimulation results show that DeepCure outperforms its competitors,producing an arresting increase of the network attack tolerance, at alower price of eliminating viruses or malicious attacks.
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