WSU Department of Computer Science Graduate Seminar ~ Dr. Mohammed Abuhamad
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Software Authorship Identification Using Deep Learning
Mohammed Abuhamad, Ph.D.
Assistant Professor of Computer Science, Loyola University Chicago
February 16, 2021
11:30 am – 12:20 pm
Software authorship identification is the process of associating a programmer to a given code based on the programmer's distinctive stylometric features. Successful software authorship de-anonymization has both software forensics applications and privacy implications. However, the process requires an efficient extraction of authorship attributes. The extraction of such attributes is very challenging due to various software code formats--- from executable binaries with different toolchain provenance to source code with different programming languages. To this end, our work proposes a deep Learning-based approach for software authorship attribution, that facilitates large-scale, format-independent, language-oblivious, and obfuscation-resilient software authorship identification. Through comprehensive experiments, the results of our work show high accuracy despite requiring a smaller number of samples per author.
Mohammed Abuhamad is an assistant professor of Computer Science at Loyola University Chicago. He received a Ph.D. degree in Computer Science from the University of Central Florida in 2020. He also received a Ph.D. degree in Electrical and Computer Engineering from INHA University in 2020. His research interests include AI/Deep-Learning-based Information Security, especially Software and Mobile/IoT Security. He is also interested in Machine Learning-based Applications and Adversarial Machine Learning. He has published several peer-reviewed research papers in top-tier conferences and journals such as ACM CCS, PoPETS, IEEE ICDCS, and IEEE IoT-J.