BotDetector: An extreme learning machine‐based Internet of Things botnet detection model. Issue 5 (16th June 2020)

• Record Type: Journal Article
• Authors: Dong, Xudong; Dong, Chen; Chen, Zhenyi; Cheng, Ye; Chen, Bo
• Other Names: Liu Ximeng guestEditor.; Mu Yi guestEditor.; Ning Jianting guestEditor.; Zhang Qingchen guestEditor.
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 32:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-16
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.3999
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: The development of artificial intelligence has brought new methods for botnet detection. For better performance, deep learning (DL) is more and more widely employed to botnet detecting. The existing DL‐based botnet detection methods require lots of computing resources and running time. While in the real Internet of Things (IoT) environment, real‐time and low computing consumption are much needed. Therefore, the DL‐based methods seem to be powerless in real‐time IoT scenarios. For these reasons, this article proposes a botnet detection model based on extreme learning machine, named BotDetector, which can directly obtain network stream files and quickly learn without data processing to extract botnet traffic characteristics. Experiments show that BotDetector has a good performance, which can identify botnets accurately with great reduction the time consumption and resource consumption. Furthermore, BotDetector has strong applicability in real IoT scenes. Abstract : This article proposes an Internet of Things (IoT) botnet detection model based on extreme learning machine (ELM), named BotDetector, which can directly obtain network stream files and quickly learn without data processing to extract botnet traffic characteristics. Experiments show that BotDetector has a good performance, which can identify botnets accurately with great reduction the time consumption and resource consumption. Furthermore, BotDetector has strong applicability.