Malware Detection And Machine Learning

1732 Words Jan 7th, 2016 7 Pages

In this chapter, we do an extensive study of malware detection and machine learning. This includes malware types, life cycle of a malware, malware analysis and detection, strategies for malware detection as well as machine learning and its types. MALWARE
Malware has been given different names and definitions. The word Malware is used to describe any form of malicious code also called malcode, malicious software or programs. One common definition of malware is the definition by McGraw and Morrisett (2000), that defines a malware as “any code added, changed, or removed from a software system in order to intentionally cause harm or subvert the intended function of the system.” Vasudevan & Yerraballi (2006) also describe malware as “a generic term that encompasses viruses, trojans, spywares and other intrusive code.” According to Christodorescu et al. (2005) any program that has a malevolent objective is a malware. Malware are generally created to compromise the confidentiality, integrity, or availability of the data/information in a computer system or network. MALWARE TYPES
One way of ensuring that the process of analysing malware is as fast as possible is by making informed hypotheses about the malware and its function. These hypotheses can then be tested. Since it is evident that better hypotheses can be made upon knowing what the malware does, some of the categories in which most malware fall into as explained by Sikorski & Honig (2012) are…
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