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Article
Algorithmically Generated Domain Detection and Malware Family Classification
Communications in Computer and Information Science
  • C. Choudhary
  • R. Sivaguru
  • M. Pereira
  • B. Yu
  • A.C. Nascimento, University of Washington Tacoma
  • M. De Cock, University of Washington Tacoma
Publication Date
1-1-2019
Document Type
Article
Abstract

In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated malicious domains and the categorization of domains according to their malware family. The datasets used for model comparison were provided by the shared task on Detecting Malicious Domain names (DMD 2018). Our models ranked first for two out of the four test datasets provided in the competition. © Springer Nature Singapore Pte Ltd. 2019.

DOI
10.1007/978-981-13-5826-5_50
Publisher Policy
pre print, post print
Citation Information
C. Choudhary, R. Sivaguru, M. Pereira, B. Yu, et al.. "Algorithmically Generated Domain Detection and Malware Family Classification" Communications in Computer and Information Science Vol. 969 (2019) p. 640 - 655
Available at: http://works.bepress.com/anderson-nascimento/26/