HTTP botnet detection using classification technique

Lee, Kher Xin (2016) HTTP botnet detection using classification technique. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

Text (Full Text) HTTP botnet detection using classification technique.pdf - Submitted Version Download (2MB)

Abstract

In this final year project, HTTP botnet was detected by using classification technique. Due to the unknown relationship between network parameter and botnet, it is difficult to detect HTTP botnet by analysis network traffic. Thus, it is requiring understanding the relationship between network parameter and botnet before classifying the malicious network traffic and non-malicious network traffic. The main objective of this project is investigating the network parameter of the network traffic. Next objective is to study the relationship between network parameter with HTTP botnet by using several classification techniques and compare which of the algorithm is more accurate for classifying the network parameter with botnet. Besides, the scopes of the investigation in this project are detecting the HTTP-based botnet only by a study on network traffic and using five type of classification technique to classify the malicious botnet traffic and non-malicious network traffic. The methodology processes of this project are literature review, data collection, pre-processing, classification and analysis and documentation. At the end of this project, it is able to identify the relationship of the network parameter with HTTP botnet and detect the HTTP botnet by classification the network parameter.

Actions (login required)

View Item