CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code

• URL: http://arxiv.org/abs/2404.15639v1
• Date: Wed, 24 Apr 2024 04:25:04 GMT
• Title: CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code
• Authors: Batu Guan, Yao Wan, Zhangqian Bi, Zheng Wang, Hongyu Zhang, Yulei Sui, Pan Zhou, Lichao Sun,
• Abstract summary: We present CodeIP, a new watermarking technique for Large Language Models (LLMs)-based code generation. CodeIP enables the insertion of multi-bit information while preserving the semantics of the generated code.
• Score: 59.32609948217718
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As Large Language Models (LLMs) are increasingly used to automate code generation, it is often desired to know if the code is AI-generated and by which model, especially for purposes like protecting intellectual property (IP) in industry and preventing academic misconduct in education. Incorporating watermarks into machine-generated content is one way to provide code provenance, but existing solutions are restricted to a single bit or lack flexibility. We present CodeIP, a new watermarking technique for LLM-based code generation. CodeIP enables the insertion of multi-bit information while preserving the semantics of the generated code, improving the strength and diversity of the inerseted watermark. This is achieved by training a type predictor to predict the subsequent grammar type of the next token to enhance the syntactical and semantic correctness of the generated code. Experiments on a real-world dataset across five programming languages showcase the effectiveness of CodeIP.

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