  Understanding the internals of Integrated Circuits (ICs), referred to as
Hardware Reverse Engineering (HRE), is of interest to both legitimate and
malicious parties. HRE is a complex process in which semi-automated steps are
interwoven with human sense-making processes. Currently, little is known about
the technical and cognitive processes which determine the success of HRE.
  This paper performs an initial investigation on how reverse engineers solve
problems, how manual and automated analysis methods interact, and which
cognitive factors play a role. We present the results of an exploratory
behavioral study with eight participants that was conducted after they had
completed a 14-week training. We explored the validity of our findings by
comparing them with the behavior (strategies applied and solution time) of an
HRE expert. The participants were observed while solving a realistic HRE task.
We tested cognitive abilities of our participants and collected large sets of
behavioral data from log files. By comparing the least and most efficient
reverse engineers, we were able to observe successful strategies. Moreover, our
analyses suggest a phase model for reverse engineering, consisting of three
phases. Our descriptive results further indicate that the cognitive factor
Working Memory (WM) might play a role in efficiently solving HRE problems. Our
exploratory study builds the foundation for future research in this topic and
outlines ideas for designing cognitively difficult countermeasures ("cognitive
obfuscation") against HRE.
