According to research, malware has grown exponentially over the last decade, causing significant financial losses to a variety of organizations and users data. Various anti-malware firms have proposed ways to protect against these malware attacks. But malware samples have been changing from time to time like changing its structure, obfuscation methods etc. Researchers and engineers have been proposing/designing different methodologies in order to comprise the threats. Machine learning and neural network methods have been used in many fields in order to solve problems and it is also used in the field of cyber security. Out of all machine learning methods ensemble learning techniques have been able to achieve highest accuracy results with minimizing the false positive rates. In this paper. Stacking algorithm (one of the ensemble learning methods) has been used in order to achieve higher results.
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