Code Generation
CODE ACROSTIC: Robust Watermarking for Code Generation
Transforming Code Integrity in LLM-Generated Content
The 'CODE ACROSTIC' method revolutionizes watermarking for LLM-generated code, directly addressing vulnerabilities like comment removal attacks. By strategically injecting watermarks into high-entropy code regions, it ensures robustness and detectability without compromising code functionality, outperforming existing techniques.
0
AUROC Improvement vs. KGW
0
Avg. TPR Drop (SOTA methods)
High
Code Usability
Deep Analysis & Enterprise Applications
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81.13%
TPR Drop for SWEET due to Comment Removal Attack (Figure 1)
Enterprise Process Flow
Cue List Construction
→
Cue Sampling (Watermark Injection)
→
Cue Detection
| Method | Pass@1 | AUROC |
|---|---|---|
| Raw LLM | 53.05 | N/A |
| Code Acrostic (Ours) | 51.20 | 0.772 (+12.70%) |
| KGW [9] | 54.27 | 0.685 |
| SWEET [10] | 54.88 | 0.692 (+1.02%) |
| EWD [11] | 54.88 | 0.750 (+9.49%) |
Robustness in Code-Only Scenarios
The paper highlights that when natural language (comments) is filtered out, Code Acrostic maintains the highest detectability, proving its robustness by embedding the watermark directly into the code structure rather than relying on textual elements. This is a significant advantage over methods like SWEET and EWD, which see a substantial drop in effectiveness in such scenarios. The proposed method ensures integrity even when code is stripped of its explanatory text.
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Your AI Implementation Roadmap
A phased approach to integrate advanced AI watermarking into your existing systems, ensuring a smooth transition and maximum impact.
Phase 01: Discovery & Strategy
Comprehensive assessment of your current infrastructure, identifying key integration points and defining a tailored AI watermarking strategy.
Phase 02: Pilot & Proof-of-Concept
Deployment of a small-scale pilot project to validate the chosen watermarking approach, measure initial performance, and gather feedback.
Phase 03: Full-Scale Integration
Seamless integration of CODE ACROSTIC into your LLM-generated code pipeline, ensuring minimal disruption and maximum security.
Phase 04: Monitoring & Optimization
Continuous monitoring of watermark detectability and system performance, with ongoing optimization to adapt to new challenges and threats.
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