Power Profiling and Analysis of Code Obfuscation for Embedded Devices

Obfuscation is a popular software transformation to protect intellectual property and avoid reverse engineering. It relies on introducing additional instructions and changing control-flow without affecting program semantics. Invariably, this introduces overheads in terms of memory, execution time and energy consumption for resource-constrained environments. In this work, we show that these overheads are dependent on three factors: the transformations and their combinations selected, the tool used to effect these transformations and the program workload. Our experiments using two popular obfuscation tools, Obfuscation Low-Level Virtual Machine (OLLVM) and Tigress, show that obfuscation could potentially lead to a 5-fold increase in execution time and energy consumption depending on these factors. Consequently, our results are profitable for security engineers to choose appropriate transformations for each application for resource-constrained environments.