当前位置:首页 > 报告详情

RTLMarker:通过硬件水印框架保护 LLM 生成的 RTL 版权.pdf

上传人: 芦苇 编号:651805 2025-05-01 24页 1.76MB

1、RTLMarker:Protecting LLM-Generated RTL Copyright via a Hardware Watermarking FrameworkKun Wang,Kaiyan Chang,Mengdi Wang,Xingqi Zou,Haobo Xu,Yinhe Han,Ying Wang*Outline Introduction Background RTLMarker Evaluation ConclusionLarge Language ModelTranslationCode GenerationChatSummarySearchReasoningLarge

2、 Language ModelRTL CodeLogic synthesisNetlistExpert-writtenHigh-level codespecificationRTL CodeLogic synthesisNetlistspecificationLarge Language ModelNature language Electronic Design Automation(EDA)flow LLM for hardware design Risks of LLMs Fake news Malicious/Vulnerable code Sensitive content Priv

3、ate data leaks Fraud Security vulnerabilityWe need to embed watermarks to RTL code generated by LLM!Outline Introduction Background RTLMarker Evaluation ConclusionLLM Watermark Text Watermark:WLLM Code Watermark:SWEETWLLM1 SWEET21 John Kirchenbauer,Jonas Geiping,Yuxin Wen,Jonathan Katz,Ian Miers,and

4、Tom Goldstein.2023.A watermark for large language models.In InternationalConference on Machine Learning.PMLR,1706117084.2 Taehyun Lee,Seokhee Hong,Jaewoo Ahn,Ilgee Hong,Hwaran Lee,Sangdoo Yun,Jamin Shin,and Gunhee Kim.2023.Who wrote this code?watermarking for code generation.arXiv preprint arXiv:230

5、5.15060(2023).LLM WatermarkEffectivenessRobustnessTransparencywatermarkTrade-offThe watermarks should be effectively embedded and detectable.The watermark should preserve the code quality and remain inconspicuous.The watermark should be resilient to common attack methods,such as string replacement a

6、ttacks.LLM Watermark Embedding watermarks to LLM-generated RTL code presents the following challenges:Existing methods cannot guarantee the correctness of the watermarked RTL code.There is a tradeoff between the transparency and effectivenessof watermarks.Watermarks at the Register Transfer Level(RT

word格式文档无特别注明外均可编辑修改,预览文件经过压缩,下载原文更清晰!
三个皮匠报告文库所有资源均是客户上传分享,仅供网友学习交流,未经上传用户书面授权,请勿作商用。
本文提出了一种保护由大型语言模型生成的硬件设计逻辑版权的硬件水印框架,名为RTLMarker。面临的风险包括假新闻、恶意/脆弱代码、敏感内容泄露等。作者提出在RTL代码中嵌入水印,以保护版权。RTLMarker框架包括规则驱动的Verilog代码转换、基于学习的水印嵌入方法,以及水印检测。实验结果显示,RTLMarker在准确性、鲁棒性和透明度方面均优于现有方法。与基准相比,RTLMarker在RTLLM基准上的准确率为95%,在VerilogEval基准上的准确率为92%。
"LLM生成RTL代码的版权保护如何实现?" "RTLMarker框架在硬件水印嵌入中的作用是什么?" "如何评估RTLMarker在水印嵌入与检测方面的有效性?"
客服
商务合作
小程序
服务号
折叠