Thwarting Piracy: Anti-debugging Using GPU-assisted Self-healing Codes
Uptycs India Pvt. Ltd., Bengaluru, India
arXiv:2210.11047 [cs.CR], (20 Oct 2022)
@misc{https://doi.org/10.48550/arxiv.2210.11047,
doi={10.48550/ARXIV.2210.11047},
url={https://arxiv.org/abs/2210.11047},
author={Mishra, Adhokshaj and Hanawal, Manjesh Kumar},
keywords={Cryptography and Security (cs.CR), FOS: Computer and information sciences, FOS: Computer and information sciences},
title={Thwarting Piracy: Anti-debugging Using GPU-assisted Self-healing Codes},
publisher={arXiv},
year={2022},
copyright={Creative Commons Attribution 4.0 International}
}
Software piracy is one of the concerns in the IT sector. Pirates leverage the debugger tools to reverse engineer the logic that verifies the license keys or bypass the entire verification process. Anti-debugging techniques are used to defeat piracy using self-healing codes. However, anti-debugging methods can be defeated when the licensing protections are limited to CPU-based implementation by writing custom codes to deactivate the anti-debugging methods. In the paper, we demonstrate how GPU implementation can prevent pirates from deactivating the anti-debugging methods by using the limitations of debugging on GPU. Generally, GPUs do not support debugging directly on the hardware, and therefore all the debugging is limited to CPU-based emulation. Also, a process running on CPU generally does not have any visibility on codes running on GPU, which comes as an added benefit for our work. We provide an implementation on GPU to show the feasibility of our method. As GPUs are getting widespread with the raise in popularity of gaming software, our technique provides a method to protect against piracy. Our method thwarts any attempts to bypass the license verification step thus offering a better anti-piracy mechanism.
October 23, 2022 by hgpu