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Paper Details
Paper Title
A Review on Malware Detection Schemes Using Machine Learning Techniques
Authors
  Priya Sharma,  Jyoti Arora
Abstract
Malware is a one type of software which can harm the computer’s operating system and may also can steal the personal information from the computer, malware can be made by using any programming language by the programmer. It is very difficult to define a malware with a single term or a single name. A malware can be consider as a malicious software or malcode or as a malicious code .Malware do the bulk of the intrusive activities on a system and that spreads itself across the hosts in a network. Malware detection techniques can be classified into 2 categories - the static analysis techniques and the dynamic analysis techniques. The static techniques involve looking into the binaries directly or the reverse engineering. The code for patterns is the same. This paper attempts to provide a brief survey of all the work that has been done in the field of malware detection. All literatures have been properly reviewed and discussed for their merits and demerits.
Keywords- Malware Detection, Machine Learning, Pattern Recognition, Signature based technique
Publication Details
Unique Identification Number - IJEDR1602028Page Number(s) - 170-172Pubished in - Volume 4 | Issue 2 | April 2016DOI (Digital Object Identifier) -    Deshbhagat Group of CollegePublisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Priya Sharma,  Jyoti Arora,   "A Review on Malware Detection Schemes Using Machine Learning Techniques", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 2, pp.170-172, April 2016, Available at :http://www.ijedr.org/papers/IJEDR1602028.pdf
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