Data Mining Techniques for Computer Virus Detection

Abstract

 Computer viruses are big threat to computer world, researchers doing work in this area have made various efforts in the direction of classification and detection methods of these viruses. Graph mining and system call arrangement are some latest research activities in this field. The computability theory and the semi computable functions are quite important in our context of analyzing malicious activity. A mathematical model like random access stored program machine with the association of attached background is used by Ferenc Leitold while explaining modeling of viruses in his paper. Computer viruses like polymorphic viruses and metamorphic viruses use more efficient techniques for their evolution so it is required to use strong models to understand their evolution and then apply detection followed by the process of removal. Code Emulation is one the strongest way to analyze computer viruses but the anti-emulation activities made by virus designers are working against it. This paper explains the data mining techniques that are used for detection of computer viruses in better manner.

Authors and Affiliations

Ankur Singh Bist

Keywords

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  • EP ID EP117264
  • DOI -
  • Views 95
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How To Cite

Ankur Singh Bist (30).  Data Mining Techniques for Computer Virus Detection. International Journal of Engineering Sciences & Research Technology, 3(1), 200-201. https://europub.co.uk/articles/-A-117264