Detection of Malware Using Machine Learning Techniques

Abstract

The subject of computer security is called malware detection, and it deals with the research and prevention of dangerous software. It's not the exclusive method of defending a company from online threats. To succeed, businesses need to assess their risk and pinpoint their weaknesses. This essay will address the rise in computer malware and how cutting-edge approaches such as behavioral-based models and signature-based models are displacing more conventional detection strategies. Future research directions in this field as well as the many methods for identifying fraudulent websites and computer viruses will be covered. To combat cyber fraud, which has increased recently, particularly in the Asia Pacific area, future instructions call for creating stronger security solutions. Traditional methods of preventing cyber-frauds and other dangerous activities from accessing computers are inadequate because of their many shortcomings. In order to tackle these problems, academics have created new techniques such as heuristic analysis and static and dynamic analysis. With no false positives or negatives, these techniques are able to identify over 90% of malware samples.