Publication Date

Spring 2018

Degree Type

Master's Project

Department

Computer Science

Abstract

This research is focused on a novel approach to detect malware based on static analysis of executable files. Specifically, we treat each executable file as a twodimensional image and use robust hashing techniques to identify whether a given executable belongs to a particular family or not. The hashing stage comprises two steps, namely, feature extraction, and compression. We compare our robust hashing approach to other machine learning-based techniques.

Available for download on Saturday, June 01, 2019

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