Details

Autor(en) / Beteiligte

• Mohd Saudi, Nur Hidayah
• Rudy Fadhlee M. D, Wan Ahmad Ramzi W. Y, Faizal M. A, Siti Rahayu Selamat

Titel

Revealing the Feature Influence in HTTP Botnet Detection

Ist Teil von

• International journal of communication networks and information security, 2022-04, Vol.9 (2)

Erscheinungsjahr

2022

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Botnet are identified as one of most emerging threats due to Cybercriminals work diligently to make most of the part of the users’ network of computers as their target. In conjunction to that, many researchers has conduct a lot of study regarding on the botnets and ways to detect botnet in network traffic. Most of them only used the feature inside the system without mentioning the feature influence in botnet detection. Selecting a significant feature are important in botnet detection as it can increase the accuracy of detection. Besides, existing research focusses more on the technique of recognition rather than uncovering the purpose behind the selection. Therefore, this paper will reveal the influence feature in botnet detection using statistical method. The result obtained showed the accuracy is about 91% which is approximately acceptable to use the influence feature in detecting botnet activity.