Detection of algorithmically generated malicious domain names using masked N-grams

作者：

Highlights：

• Detection of algorithmically generated domains using masked N-grams is introduced.

• Dataset of algorithmically generated domains of real malware is publicly released.

• Malware families are classified according to their domain generation algorithm.

• Masked N-grams provide a good trade-off between training time and accuracy.

摘要

•Detection of algorithmically generated domains using masked N-grams is introduced.•Dataset of algorithmically generated domains of real malware is publicly released.•Malware families are classified according to their domain generation algorithm.•Masked N-grams provide a good trade-off between training time and accuracy.

论文关键词：Random Forest,Malware,Domain-generated algorithms

论文评审过程：Received 28 February 2018, Revised 18 January 2019, Accepted 19 January 2019, Available online 24 January 2019, Version of Record 28 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.050