Document Details

Document Type : Thesis 
Document Title :
SOFTWARE DEFINED NETWORK (SDN) APPROACH TO DETECT AND REACT TO MALWARE PROPAGATION IN LARGE SCALE NETWORK
استخدام شبكات SDN لاكتشاف البرمجيات الخبيثة والحد من انتشارها في الشبكات واسعة النطاق
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : In a large-scale network, the network intrusion deploys quickly and has a signif- icant impact on the availability of services, making the spread of intrusions one of the more pressing problems to be solved in network security. Recent years, software-defined networking (SDN) considered a promising technology to facili- tate network management as well as enhance network security. Due to the SDN architecture, it provides a global and centralized view of network states to the con- troller. As well as the programmability support the application of different security defence for variant types of attacks. The existing SDN-based defence systems face many challenges such as low detection accuracy due to the high false alarms, controller overhead and single point of failure. In this research, we develop a distributed framework based on SDN multi-controller able to detect attacks on high volume traffic networks. The system combines machine learning detection method and statistical detection methods to provide accurate detection accuracy with minimum controller response time as possible. The experiments show that our system can effectively detect the attack with an extremely low of both false alarm and detection delay 
Supervisor : Prof. Ahmed Barnawi 
Thesis Type : Master Thesis 
Publishing Year : 1441 AH
2019 AD 
Added Date : Monday, December 9, 2019 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
غدير عبيد الشريفAlsharif, Ghadeer ObaidResearcherMaster 

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 45656.pdf pdf 

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