Chunlai Du1, Shenghui Liu1, Lei Si2, Yanhui Guo2, *, Tong Jin1
CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1785-1796, 2020, DOI:10.32604/cmc.2020.010091
- 30 June 2020
Abstract In recent years, the number of exposed vulnerabilities has grown rapidly and
more and more attacks occurred to intrude on the target computers using these
vulnerabilities such as different malware. Malware detection has attracted more attention
and still faces severe challenges. As malware detection based traditional machine
learning relies on exports’ experience to design efficient features to distinguish different
malware, it causes bottleneck on feature engineer and is also time-consuming to find
efficient features. Due to its promising ability in automatically proposing and selecting
significant features, deep learning has gradually become a research hotspot. In More >
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