Useing machine learning algorithms to detect DRDoS attacks on UDP-based services within SDN

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Useing machine learning algorithms to detect DRDoS attacks on UDP-based services within SDN

ارائه دهنده: Provider: mitra akbari kohnehshahri

اساتید راهنما: Supervisors: Dr. Mohammad Nasiri

اساتید مشاور: Advisory Professors: Dr.Reza Mohammadi

اساتید ممتحن یا داور: Examining professors or referees: Dr. Moharam Mansoori zadeh,Dr.hatam abdoli

زمان و تاریخ ارائه: Time and date of presentation: 1400.08.01

مکان ارائه: Place of presentation: virtual

چکیده: Abstract: With the development of mobile systems and peripherals, as well as the emergence of new ideas such as cloud computing and big data, and most importantly, the increase in the population of networked users need to review the current network architecture and its development and progress more It is already considered. One rapidly evolving solution to these challenges today is software defined networks. Software defined networks are a new and unique architecture in the network, in which data plane and control plane are independent of each other and each is programmed directly. Due to the centralized view of software defined networks, this type of network has a more general and comprehensive view of the network, which in case of attacks that are created for malicious purposes, including enhanced attacks of softwaredefined networks, efficiency They show better, dns amplification attacks have a larger response size than the request, in an enhanced attack the attacker forges the victim's address as the source address, and the responses instead reach the attacker. They go to the victim and therefore it is more difficult to detect this type of attack in traditional networks, but by using the centralized view of software defined networks, it is possible to have a good result in detecting these attacks. There are several ways to detect such attacks, one of which is to use machine learning algorithms. In this regard, in this study, the purpose of online detection of distributed denial of service attacks based on reflection using machine learning algorithms that machine learning method is one of the methods to detect this type of attack

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