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Mitigating DDoS Using BOTNET Analysis with Flow Anomaly Detection

Baradaran Jafari, Navid | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 50010 (56)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Jafari, Mahdi; Endicott-Popovsky, Barbara
  7. Abstract:
  8. Internet is the largest multi-purpose, self-reliant, complex and distributed computer network across the globe. The nodes of this network are placed in every place like homes, offices, military camps, schools and all other locations by utilizing many different communication protocols, media and capacities. Furthermore, by rapid technology development, there are many newly born applications utilizing internet in new ways such as Internet of Things systems. The explosive growth of technology causing accelerated addition of new nodes to the internet, and any new single node may have several new unpatched vulnerabilities. This is a serious issue for managing this vast chaotic configuration and this level of heterogenous complexity causing high potentials of abuse, due to controlling, tracking and tracing difficulties. BOTNET is only one of the issues addressed above that will form an overlay network of infected nodes by several means and will serve her BOTMASTER to execute commands, mostly launching well-formed coordinated global attacks, known as DDOS (Distributed Denial of Service). To cope with the mentioned problem, I evaluated a combination of solutions utilizing SDN capabilities to spot the attack, then act to take back control and minimize the impacts by isolating BOT agents in a flow-aware consensus based decision making in SDN network
  9. Keywords:
  10. Distributed Denial of Service (DDOS)Attack ; Botnet Network ; Software Defined Networks (SDN) ; Botnet Networks Detection ; OpenFlow Protocol ; Data Stream Clustering

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