Malware Detection Using Machine Learning

Download Now
Provided by: University of Hyderabad
Topic: Security
Format: PDF
The authors propose a versatile framework in which one can employ different machine learning algorithms to successfully distinguish between malware files and clean files, while aiming to minimize the number of false positives. In this paper, they present the ideas behind their framework by working firstly with cascade one-sided perceptrons and secondly with cascade kernelized one-sided perceptrons. After having been successfully tested on medium-size datasets of malware and clean files, the ideas behind this framework were submitted to a scaling-up process that enable the user to work with very large datasets of malware and clean files.
Download Now

Find By Topic