Document Details

Document Type : Thesis 
Document Title :
GENERAL BOTNET DETECTION BASED ON NETWORK AND HOST ANALYSIS
كشف البوت نت على أساس تحليل المعلومات في الشبكة و جهاز المستخدم
 
Subject : FACULTY OF COMPUTING AND INFORMATION TECHNOLOGY 
Document Language : Arabic 
Abstract : One of the most serious cyber-security threats is the botnet. The botnet runs in the background of the compromised machine and maintains communication with the C\&C server to receive malicious commands. Malicious activity is executed without the knowledge of the owner of the compromised computer. Botnet master uses botnet to launch dangerous attacks such as Distributed Denial of Service (DDoS), finishing, Data stealing, Click fraud and spamming. The size of the botnet is usually very large and millions of infected hosts may belong to it. This thesis addresses the problem of detecting botnet flows records within Netflow traces and activities in the host. We propose a general technique that is capable of detecting a new botnet in early stages. Our technique can be implement at three level: the host level, the network level or a combination of both. The botnet communication traffic we are interested in includes HTTP, P2P, IRC and DNS using IP fluxing. The proposed technique has been evaluated with a collection of real malicious and legitimate datasets. HANABot algorithm is proposed to preprocess and extracted features to differentiate the botnet behavior from the legitimate behavior. The results of our experiment show a high level of accuracy and a low positive rate. Furthermore, a comparison between some existing approaches was given, focusing on specific features and performance. The proposed technique outperforms some of the presented approaches in terms of accurately detecting botnet flow records within Netflow traces. 
Supervisor : Dr. Saoucene Alaye Mahfoudh 
Thesis Type : Master Thesis 
Publishing Year : 1437 AH
2016 AD 
Added Date : Monday, July 25, 2016 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
سوزان بندر المطيريAl Mutairi, Suzan BandarResearcherMaster 

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