Tukkappa K Gundoor
Research Scholar, Department of Computer Science, Karnatak University, Dharwad, India
Sridevi
Professor, Department of Computer Science, Karnatak University, Dharwad, India
Abstract
Malware is a program that executes harmful acts and steals information. nowadays it is widely recognized as one of the largest hazards. In this research work machine learning is used to identify and detect Non-PE file features. The various distinct aspects of the Non-PE files features can correlate with one another, being clean or affected, led to the identification of such features. by using machine learning algorithms such as Ada Boost Classifier, Gaussian NB, KN Classifier, RF Classifier, SGD classifier, and feature selection produced the best detection rate also Prediction accuracy of the algorithms is used to compare the efficacy and efficiency
Keywords- Benign, Classifiers, Feature selection, Malware, Non-portable malware, Random Forest.