A hybrid streaming analytic model for detection and classification of malware using Artificial Intelligence techniques

Abstract

In this era of technology and network, the battleship between security experts and malware developers is a never-ending fight as every day a new signatures malware comes into the battle to fight. To compete in this technological battle, AI-based technique would effectively combat and triumph. Various machine learning and deep learning techniques involved in the process of malware detection and classification with good accuracy are analyzed. ML-based techniques perform very well and were able to detect and classify even zero-day malware. A new hybrid methodology for the efficient detection and classification of malware is proposed. The accuracy of malware detection is improved by the proposed ensemble method.