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Automated reverse engineering using lego

Georg Chalupar, Stefan Peherstorfer, Erik Poll, Joeri de Ruiter

Year
2014
Citations
34

Abstract

State machine learning is a useful technique for automating reverse engineering. In essence, it involves fuzzing different sequences of inputs for a system. We show that this technique can be successfully used to reverse engineer hand-held smartcard readers for Internet banking, by using a Lego robot to operate these devices. In particular, the state machines that are automatically inferred by the robot reveal a security vulnerability in one such a device, the e.dentifier2, that was previously discovered by manual analysis, and confirm the absence of this flaw in an updated version of this device.

Keywords

Reverse engineeringFuzz testingComputer scienceState (computer science)RobotArtificial intelligenceThe InternetSoftware engineeringFinite-state machineOperating system

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