CapJack: Capture In-Browser Crypto-jacking by Deep Capsule Network through Behavioral Analysis

Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Liuwan Zhu, Hongyi Wu

Abstract: This work proposes an innovative approach, named CapJack, to detect in-browser malicious cryptocurrency mining activities by using the latest CapsNet technology. To the best of our knowledge, this is the first work to introduce CapsNet to the field of malware detection through system behavioral analysis. It is particularly effective to detect malicious miners under multitasking environments where multiple applications run simultaneously. Experimental data show appealing performance of CapJack, with a detection rate of as high as 87% instantly and 99% within a window of 11 seconds.