%0 Journal Article
%T Targeted Local Immunization in Scale-Free Peer-to-Peer Networks
%A Xin-Li Huang
%A Fu-Tai Zou
%A Fan-Yuan Ma
%A <br>Xin-Li Huang
%A Fu-Tai Zou
%A and Fan-Yuan Ma
%J 计算机科学技术学报
%D 2007
%I 
%X The power-law node degree distributions of peer-to-peer overlay networks make them extremely robust to random failures whereas highly vulnerable under intentional targeted attacks. To enhance attack survivability of these networks, DeepCure, a novel heuristic immunization strategy, is proposed to conduct decentralized but targeted immunization. Different from existing strategies, DeepCure identifies immunization targets as not only the highly-connected nodes but also the nodes with high availability and/or high link load, with the aim of injecting immunization information into just right targets to cure. To better trade off the cost and the efficiency, DeepCure deliberately select these targets from 2-local neighborhood, as well as topologically-remote but semantically-close friends if needed. To remedy the weakness of existing strategies in case of sudden epidemic outbreak, DeepCure is also coupled with a local-hub oriented rate throttling mechanism to enforce proactive rate control. Extensive simulation results show that DeepCure outperforms its competitors, producing an arresting increase of the network attack tolerance, at a lower price of eliminating viruses or malicious attacks.
%K targeted local immunization
%K peer-to-peer networks
%K overlay topology
%K scale-free
%K cost
%K efficiency
%K rate control<br>P2P网络
%K 无尺度网络
%K 靶向局部免疫
%K 重叠拓扑
%K 成本
%K 效率
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=F57FEF5FAEE544283F43708D560ABF1B&aid=CBCDFFE5AEBDB1BF6CAB01A5AC3315FD&yid=A732AF04DDA03BB3&vid=BC12EA701C895178&iid=38B194292C032A66&sid=D0E8F9CBDBE0070C&eid=3FC4D669D19FF0C6&journal_id=1000-9000&journal_name=计算机科学技术学报&referenced_num=0&reference_num=48