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CT-ISG: Collaborative research: Enabling Routers to Detect and Filter Spoofed Traffic

CT-ISG: Collaborative research: Enabling Routers to Detect and Filter Spoofed Traffic
CT-ISG:协作研究:使路由器能够检测和过滤欺骗流量
批准号:
0716452
负责人:
Jelena Mirkovic
金额:
$20.47万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-08-01 至 2008-04-30

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英文摘要
0716452Jelena MirkovicUniversity of Delaware0716829Peter ReiherUCLACT-ISG: Collaborative Research: Enabling Routers to Detect and Filter Spoofed TrafficIP spoofing exacerbates many security threats.If spoofing were eliminated or sufficiently reduced, defenses against DDoS, distributed scanning and intrusions would be much simplified and more effective. Of particular interest are spoofing defenses that will be both practical (cheap to deploy and operate) and effective (provide significant benefit in sparse deployment. This project develops two such defense mechanisms: (1) Clouseau, which enables routers on asymmetric paths to accurately infer associations between the route descriptor and the source address. It will support multiple associations (in case of multipath routing) and will promptly update associations when routes change. Clouseau will be integrated with two very effective spoofing defenses: route-based filtering and hop-count filtering, and will protect deploying networks from spoofed traffic. (2) RAD, which helps networks protect themselves from reflector attacks.Clouseau and RAD will operate completely autonomously. Deployment of Clouseau at as few as 50 chosen Internet autonomous systems, together with RBF or HCF, will reduce amount of spoofed traffic on the Internet to less than 3%. In isolated deployment, Clouseau with RBF or HCF will reduce spoofed traffic received by the deploying network to less than 3%. RAD system will offer a significant protection from reflector attacks in isolated deployment and an almost perfect protection when RAD is deployed in the Internet core. This research is leading to a significant reduction of spoofed traffic in the Internet. All code will be released to the public, and graduate and undergraduate students will receive valuable training from participation in this project.
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