Design and Evaluation of Software Obfuscations

PhD Thesis (final version: 15 September 2008)
Anirban Majumdar

Abstract

Software obfuscation is a protection technique for making code unintelligible to automated program comprehension and analysis tools. It works by performing semantic preserving transformations such that the difficulty of automatically extracting the computational logic out of code is increased. Obfuscating transforms in existing literature have been designed with the ambitious goal of being resilient against all possible reverse engineering attacks. Even though some of the constructions are based on intractable computational problems, we do not know, in practice, how to generate hard instances of obfuscated problems such that all forms of program analyses would fail.

In this thesis, we address the problem of software protection by developing a weaker notion of obfuscation under which it is not required to guarantee an absolute blackbox security. Using this notion, we develop provably-correct obfuscating transforms using dependencies existing within program structures and indeterminacies in communication characteristics between programs in a distributed computing environment. We show how several well known static analysis tools can be used for reverse engineering obfuscating transforms that derive resilience from computationally hard problems. In particular, we restrict ourselves to one common and potent static analysis tool, the static slicer, and use it as our attack tool. We show the use of derived software engineering metrics to indicate the degree of success or failure of a slicer attack on a piece of obfuscated code. We address the issue of proving correctness of obfuscating transforms by adapting existing proof techniques for functional program refinement and communicating sequential processes.

The results of this thesis could be used for future work in two ways: first, future researchers may extend our proposed techniques to design obfuscations using a wider range of dependencies that exist between dynamic program structures. Our restricted attack model using one static analysis tool can also be relaxed and obfuscations capable of withstanding a broader class of static and dynamic analysis attacks could be developed based on the same principles. Secondly, our obfuscatory strength evaluation techniques could guide anti-malware researchers in the development of tools to detect obfuscated strains of polymorphic viruses.