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Home / programming language / Online Java Projects / A Collaborative DDoS Defence Framework using Network Function Virtualization
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A Collaborative DDoS Defence Framework using Network Function Virtualization

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SKU: PROJ8101 Categories: 2018-2019 Projects, Digital Image Processing Projects, Online Java Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Matlab Project, PHP Project, Students Projects
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A Collaborative DDoS Defence Framework using Network Function Virtualization

Abstract-High-profile, and often destructive Distributed Denial of Service (DDoS) attacks continue to be one of the top security concerns as the DDoS attacks volumes are increasing constantly. Among them the SYN Flood attack is the most common type. Conventional DDoS defense solutions may not bepreferable since they demand highly capable hardware resources which induces high cost and long deployment cycle. The emerging of Network Function Virtualization (NFV) technology introduces new opportunities to decrease the amount of proprietary hardware that is needed to launch and operate network services. In this paper, we propose a DDoS defense mechanism named CoFence which facilitates a “domain-helps-domain” collaboration network among NFV-based domain networks. CoFence allows domain networks to help each other in handling large volume of DDoS attacks through resource sharing. Specifically,
we design a dynamic resource allocation mechanism for domains so that the resource allocation is fair, efficient, and incentivecompatible. The resource sharing mechanism is modeled as a multi-leader-follower Stackelberg game. In this game all domains have a degree of control to maximize their own utility. The resource supplier domains determine the amount of resource to each requesting peer based on optimizing a reciprocal-based utility function. On the other hand, the resource requesting domains decide the level of demand to send to the resource supplier domains in order to reach sufficient support. Our simulation results demonstrate that the designed resource allocation game is effective, incentive compatible, fair, and reciprocal under its Nash Equilibrium

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