LAUSR

In cyber-physical additive manufacturing systems, side-channel attacks have been used to reconstruct the G/M-code (which are instructions given to a manufacturing system) of 3D objects being produced. This method is effective for stealing intellectual property from an organization, through least expected means, during prototyping stage before the product goes through a large-scale fabrication and comes out in the market. However, an attacker can be far from being able to completely reconstruct the G/M-code due to lack of enough information leakage through the side-channels. In this paper, we propose a novel way to amplify the information leakage and thus boost the chances of recovery of G/M-code by surreptitiously altering the compiler. By using this compiler, an adversary may easily control various parameters to magnify the leakage of information from a 3D printer while still producing the desired object, thus remaining hidden from the authentic users. This type of attack may be implemented by strong attackers having access to the tool chain and seeking high level of stealth. We have implemented such a compiler and have demonstrated that it increases the success rate of recovering G/M-codes from the four side-channels (acoustic, power, vibration, and electromagnetic) by up to 39 percent compared to previously proposed attacks.