Publication Date
Spring 2018
Degree Type
Master's Project
Degree Name
Master of Science (MS)
Department
Computer Science
Abstract
Recent research indicates that effective malware detection can be implemented based on analyzing portable executable (PE) file headers. Such research typically relies on prior knowledge of the header to extract relevant features. However, it is also possible to consider the entire header as a whole, and use this directly to determine whether the file is malware. In this research, we collect a large and diverse malware data set. We then analyze the effectiveness of various machine learning techniques based on PE headers to classify the malware samples. We compare the accuracy and efficiency of each technique considered.
Recommended Citation
Kim, Samuel, "PE Header Analysis for Malware Detection" (2018). Master's Projects. 624.
DOI: https://doi.org/10.31979/etd.q3dd-gp9u
https://scholarworks.sjsu.edu/etd_projects/624
