Alan C. Lin

Date of Award


Document Type


Degree Name

Master of Science in Computer Science


Department of Electrical and Computer Engineering

First Advisor

J. Todd McDonald, PhD


Software protection is of great interest to commercial industry. Millions of dollars and years of research are invested in the development of proprietary algorithms used in software programs. A reverse engineer that successfully reverses another company‘s proprietary algorithms can develop a competing product to market in less time and with less money. The threat is even greater in military applications where adversarial reversers can use reverse engineering on unprotected military software to compromise capabilities on the field or develop their own capabilities with significantly less resources. Thus, it is vital to protect software, especially the software’s sensitive internal algorithms, from adversarial analysis. Software protection through obfuscation is a relatively new research initiative. The mathematical and security community have yet to agree upon a model to describe the problem let alone the metrics used to evaluate the practical solutions proposed by computer scientists. We propose evaluating solutions to obfuscation under the intent protection model, a combination of white-box and black-box protection to reflect how reverse engineers analyze programs using a combination white-box and black-box attacks. In addition, we explore use of experimental methods and metrics in analogous and more mature fields of study such as hardware circuits and cryptography. Finally, we implement a solution under the intent protection model that demonstrates application of the methods and evaluation using the metrics adapted from the aforementioned fields of study to reflect the unique challenges in a software-only software protection technique.

AFIT Designator


DTIC Accession Number