  This study addresses the challenge of reverse engineering binaries from
unknown instruction set architectures, a complex task with potential
implications for software maintenance and cyber-security. We focus on the tasks
of detecting candidate call and return opcodes for automatic extraction of call
graphs in order to simplify the reverse engineering process. Empirical testing
on a small dataset of binary files from different architectures demonstrates
that the approach can accurately detect specific opcodes under conditions of
noisy data. The method lays the groundwork for a valuable tool for reverse
engineering where the reverse engineer has minimal a priori knowledge of the
underlying instruction set architecture.
