Design and implementation of a data mining system for malware detection

Bhavani Thuraisingham, Tahseen Al-Khatib, Latifur Khan, Mehedy Masud, Kevin Hamlen, Vaibhav Khadilkar, Satyen Abrol

Research output: Contribution to journalArticlepeer-review


This paper describes the design and implementation of a data mining system called SNODMAL (Stream based novel class detection for malware) for malware detection. SNODMAL extends our data mining system called SNOD (Stream-based Novel Class Detection) for detecting malware. SNOD is a powerful system as it can detect novel classes. We also describe the design of SNODMAL++ which is an extended version of SNODMAL.

Original languageEnglish
Pages (from-to)33-49
Number of pages17
JournalJournal of Integrated Design and Process Science
Issue number2
Publication statusPublished - 2012
Externally publishedYes


  • Data mining
  • machine learning
  • malware detection
  • stream-based novel class detection
  • streambased classification

ASJC Scopus subject areas

  • General Engineering


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