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Research On Intelligent Mitigation Of DDoS For Information Centirc Network

Posted on:2020-11-06Degree:MasterType:Thesis
Country:ChinaCandidate:W Y HanFull Text:PDF
GTID:2428330623963748Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
Information-Centric Networking(ICN)is a novel communication paradigm that focuses on content retrieval regardless of the content source location.Currently,trust is more and more important and including content protection as well as node protection.Especially in ICN,content-driven trust management is lacked.Every node can access ICN,request and publish content.ICN is inherently secure,but it still has the risk to be attacked.In addition,because there is no trust management system,we can't distinguish the content credibility of node requests or publications.ICN is especially vulnerable to distributed denial of service(DDo S)attacks.Resilience to DDo S attacks that plague today's Internet is a major issue for any new architecture and deserves full attention.What's more,ICN changes the security model from securing the path to securing the content,which is available to all the ICN nodes as ICN users could benefit from any available copy.As a result of that,current security strategies lose efficiency and it is more difficult to defend DDo S attack on account that it's hard to locate the attacker.There is a strong requirement of establishment of trust framework in ICN.In this paper,we propose a DDo S attack intelligence mitigation scheme for information center networks.We designed a novel contentdriven CA that focuses on ICN node credit authentication to prevent malicious nodes from accessing and preventing them from occupying.Moreover,our proposed intelligent mitigation solution for DDo S attacks is based on the SDN architecture and provides an extensible machine learning decision algorithm.On this basis,we also designed a software-defined onpath time synchronization scheme to optimize and improve the proposed mitigation mechanism.Finally,we verify the effectiveness of our proposed scheme through simulation results.
Keywords/Search Tags:Information-Centric Networking, Software-defined network, machine learning, trust management system
PDF Full Text Request
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