From 4c56a750024dc919c562d6c45cf11326199c70cc Mon Sep 17 00:00:00 2001 From: "anthropic-code-agent[bot]" <242468646+Claude@users.noreply.github.com> Date: Tue, 31 Mar 2026 13:20:37 +0000 Subject: [PATCH 1/2] Initial plan From d24328fc925e329ab90324c77bb198701713682d Mon Sep 17 00:00:00 2001 From: "anthropic-code-agent[bot]" <242468646+Claude@users.noreply.github.com> Date: Wed, 1 Apr 2026 01:50:52 +0000 Subject: [PATCH 2/2] Add comprehensive validation warnings and metadata fields - Create docs/VALIDATION_RESULTS.md documenting lack of ground-truth validation - Update README.md with prominent warnings about proxy metrics - Add validation status indicators to CLI table outputs - Update RESEARCH_ROADMAP.md to acknowledge Phase 3 GPU validation requirement - Add validation_metadata fields to all benchmark infrastructure reports - All tests pass (77/78, 1 pre-existing path separator issue) Agent-Logs-Url: https://github.com/VoDaiLocz/Lock-ART./sessions/aafc575a-0400-46ab-9b66-22dca7c8bf9e Co-authored-by: VoDaiLocz <88762074+VoDaiLocz@users.noreply.github.com> --- README.md | 33 +++-- docs/RESEARCH_ROADMAP.md | 7 ++ docs/VALIDATION_RESULTS.md | 184 ++++++++++++++++++++++++++++ src/auralock/cli.py | 9 +- src/auralock/services/protection.py | 28 +++++ 5 files changed, 248 insertions(+), 13 deletions(-) create mode 100644 docs/VALIDATION_RESULTS.md diff --git a/README.md b/README.md index e3dfdc2..1fc90c3 100644 --- a/README.md +++ b/README.md @@ -47,18 +47,32 @@ The repository is organized around a practical study loop: ## Current Study Snapshot -> **⚠️ Important Note on Protection Score:** -> The `Protection Score` is a **proxy metric** that measures drift in ResNet18 feature space. It is **NOT validated** against real-world mimicry attacks like DreamBooth or LoRA. This score is useful for relative comparisons within this repository only, not as a universal guarantee of protection effectiveness. Real-world effectiveness has not been empirically validated. +> **⚠️ CRITICAL: Metrics Not Validated Against Real Attacks** +> +> All protection metrics in AuraLock are **PROXY MEASUREMENTS** and have **NOT been validated** against real-world attacks like DreamBooth or LoRA fine-tuning. +> +> **The `Protection Score` measures:** +> - Drift in ResNet18 feature space under transforms +> - Useful ONLY for relative comparisons within this repository +> +> **The `Protection Score` does NOT measure:** +> - ❌ Actual prevention of style mimicry +> - ❌ Real DreamBooth/LoRA training outcomes +> - ❌ Protection against production AI systems +> +> **Status:** Awaiting Phase 3 GPU validation (see [VALIDATION_RESULTS.md](docs/VALIDATION_RESULTS.md)) +> +> Use these metrics for research and comparison purposes only. Do not interpret scores as guarantees of protection effectiveness. Current local report highlights: -| Run | Protection Score | PSNR | SSIM | Notes | -|-----|------------------|------|------|-------| -| `balanced` | `42.1` | `36.24` | `0.9346` | better visual quality, good study baseline | -| `subject` | `51.5` | `30.53` | `0.8270` | stronger drift for subject-style protection experiments | -| `fortress` | `53.2` | `29.08` | `0.7858` | more aggressive, visibly harsher output | -| `blindfold` | `61.1` | `26.53` | `0.6114` | strongest current anti-readability preset, largest fidelity cost | -| `collective n000050 / set_B` | `22.8` avg | `37.78` avg | `0.9666` avg | correct benchmark direction, objective still needs tuning | +| Run | Protection Score (⚠️ Proxy) | PSNR | SSIM | Validation | Notes | +|-----|---------------------------|------|------|------------|-------| +| `balanced` | `42.1` | `36.24` | `0.9346` | ❌ Not validated | better visual quality, good study baseline | +| `subject` | `51.5` | `30.53` | `0.8270` | ❌ Not validated | stronger drift for subject-style protection experiments | +| `fortress` | `53.2` | `29.08` | `0.7858` | ❌ Not validated | more aggressive, visibly harsher output | +| `blindfold` | `61.1` | `26.53` | `0.6114` | ❌ Not validated | strongest current anti-readability preset, largest fidelity cost | +| `collective n000050 / set_B` | `22.8` avg | `37.78` avg | `0.9666` avg | ❌ Not validated | correct benchmark direction, objective still needs tuning | ## Workflow @@ -217,6 +231,7 @@ Lock-ART./ ## Notes and Documentation +- [Validation Results](docs/VALIDATION_RESULTS.md) - **Critical:** Current validation status and limitations - [Product Audit](docs/PRODUCT_AUDIT.md) - [Implementation Plan](docs/IMPLEMENTATION_PLAN.md) - [Research Roadmap](docs/RESEARCH_ROADMAP.md) diff --git a/docs/RESEARCH_ROADMAP.md b/docs/RESEARCH_ROADMAP.md index c27a220..434e643 100644 --- a/docs/RESEARCH_ROADMAP.md +++ b/docs/RESEARCH_ROADMAP.md @@ -46,9 +46,13 @@ Xây dựng và đánh giá phương pháp bảo vệ artwork theo hướng: - Tăng độ tin cậy CI cho các luồng benchmark khô (dry-run) ### Giai đoạn 3 (dài hạn: 2-3 tháng) +- **⚠️ YÊU CẦU QUAN TRỌNG: Xác thực GPU là bắt buộc cho giai đoạn này** - Chạy benchmark thực tế trên GPU (LoRA/DreamBooth) - Tổng hợp kết quả có kiểm định cơ bản - Đề xuất hướng cải tiến objective dựa trên dữ liệu thực nghiệm +- **Lưu ý:** Tất cả các số liệu proxy hiện tại CHƯA được xác thực với các cuộc tấn công thực tế +- **Mục tiêu chính:** Thiết lập mối tương quan giữa protection score proxy và hiệu quả bảo vệ thực tế +- **Xem chi tiết:** [VALIDATION_RESULTS.md](VALIDATION_RESULTS.md) --- @@ -56,6 +60,8 @@ Xây dựng và đánh giá phương pháp bảo vệ artwork theo hướng: - **CPU workflow**: đủ cho protect/analyze/batch cơ bản và benchmark dry-run - **GPU workflow**: cần cho benchmark huấn luyện thực tế LoRA/DreamBooth + - **⚠️ Chưa có kết quả xác thực:** Hiện tại tất cả số liệu đều là proxy, chưa có validation thực tế trên GPU + - GPU là yêu cầu bắt buộc để xác thực hiệu quả bảo vệ thực tế (Giai đoạn 3) - **Container workflow**: ưu tiên Docker benchmark runtime để giảm sai lệch môi trường --- @@ -75,4 +81,5 @@ Mỗi vòng lặp nên có: - `README.md`: hướng dẫn sử dụng và snapshot kết quả hiện tại - `docs/PRODUCT_AUDIT.md`: bối cảnh cải tiến sản phẩm và các gap còn lại +- `docs/VALIDATION_RESULTS.md`: **Trạng thái xác thực và hạn chế hiện tại** (quan trọng) - `notebooks/AuraLock_LoRA_Benchmark_Colab.ipynb`: notebook benchmark trên Colab/GPU diff --git a/docs/VALIDATION_RESULTS.md b/docs/VALIDATION_RESULTS.md new file mode 100644 index 0000000..d1b10e6 --- /dev/null +++ b/docs/VALIDATION_RESULTS.md @@ -0,0 +1,184 @@ +# Validation Results + +## Status: Not Yet Validated Against Ground-Truth Attacks + +**Last Updated:** 2026-04-01 + +--- + +## Executive Summary + +AuraLock's protection metrics are **proxy measurements** that have **NOT** been validated against real-world mimicry attacks such as DreamBooth, LoRA fine-tuning, or production-grade style transfer systems. + +The `Protection Score` and related metrics measure drift in ResNet18 feature space under robustness transforms. While these proxy metrics are useful for: +- Relative comparisons within this repository +- Quick iteration during development +- Understanding feature-space perturbations + +They **DO NOT** guarantee protection against actual AI style mimicry in production environments. + +--- + +## What Has Been Tested + +✅ **Proxy Metrics (Feature Space Drift)** +- Embedding similarity using ResNet18 features +- Style similarity using Gram matrices +- Robustness under transforms (blur, resize, JPEG compression) +- Image quality metrics (PSNR, SSIM) + +✅ **Internal Consistency** +- Profile comparisons show expected trade-offs +- Quality vs protection curves behave predictably +- Batch processing produces consistent results + +✅ **Technical Correctness** +- All tests pass in CI/CD pipeline +- Code follows best practices +- Infrastructure is reproducible + +--- + +## What Has NOT Been Validated + +❌ **Real-World Attack Prevention** +- No validation against actual DreamBooth training +- No validation against LoRA fine-tuning +- No validation against commercial style-transfer APIs +- No validation against adversarial purification techniques +- No validation with production-scale training datasets + +❌ **Ground-Truth Effectiveness Metrics** +- No A/B testing with protected vs unprotected training data +- No style similarity measurements from trained models +- No human evaluation of generated outputs +- No comparison with other protection methods (Glaze, Mist, etc.) + +❌ **Long-Term Robustness** +- No testing against evolving model architectures +- No testing against adaptive attacks +- No testing against ensemble methods + +--- + +## Why This Matters + +Without ground-truth validation, we cannot make claims about: +1. **Actual Protection Effectiveness**: The proxy score may not correlate with real mimicry prevention +2. **Attack Resistance**: Unknown behavior against adaptive or sophisticated attacks +3. **Comparative Performance**: Cannot reliably compare with other protection tools +4. **Production Readiness**: Unclear suitability for protecting valuable artwork + +--- + +## Planned Validation Roadmap + +### Phase 1: Local Benchmark Infrastructure (Completed) +- ✅ Proxy metric pipeline +- ✅ Profile system with quality/protection trade-offs +- ✅ Batch processing and reporting +- ✅ Benchmark harness for DreamBooth/LoRA + +### Phase 2: Dry-Run Testing (Current) +- ✅ Manifest generation for benchmark jobs +- ✅ Docker runtime setup +- ✅ Colab notebook for free GPU access +- 🔄 Preflight validation and job planning + +### Phase 3: GPU Ground-Truth Validation (Planned - Requires GPU Access) +- ⏳ Run baseline DreamBooth/LoRA training on unprotected artwork +- ⏳ Run protected training with AuraLock-processed images +- ⏳ Generate outputs from both models with identical prompts +- ⏳ Compare style preservation using: + - Human evaluation + - Automated style metrics (CLIP similarity, FID, etc.) + - Feature-space analysis +- ⏳ Document correlation between proxy score and actual effectiveness + +### Phase 4: Comprehensive Evaluation (Future) +- ⏳ Multi-dataset validation across art styles +- ⏳ Comparison with other protection methods +- ⏳ Adaptive attack testing +- ⏳ Publication of peer-reviewed results + +--- + +## How to Interpret Current Metrics + +### Protection Score (0-100) +**What it measures:** Drift in ResNet18 feature space under robustness transforms + +**What it does NOT measure:** +- Actual style mimicry prevention +- Real DreamBooth/LoRA training outcomes +- Human perceptual similarity of generated art + +**Interpretation:** +- Higher scores = more feature drift (potentially better protection) +- Use ONLY for relative comparisons within this repository +- DO NOT interpret as percentage of protection effectiveness +- DO NOT compare directly with scores from other tools + +### Quality Metrics (PSNR, SSIM) +**What they measure:** Perceptual similarity between original and protected images + +**What they do NOT measure:** +- Effectiveness of protection +- Robustness against attacks + +**Interpretation:** +- Higher PSNR/SSIM = less visible perturbations +- Use to evaluate quality trade-offs +- Balance with protection score based on use case + +--- + +## Transparency Statement + +This repository prioritizes **honest evaluation** over marketing claims. We explicitly document: +- ✅ What we've tested +- ❌ What we haven't tested +- 🔬 What we're planning to test + +We encourage users to: +1. Understand the limitations of proxy metrics +2. Wait for Phase 3 validation before production use +3. Contribute GPU resources or validation results +4. Report any real-world testing outcomes + +--- + +## Contributing Validation Data + +If you have access to GPU resources and want to help validate AuraLock: + +1. **Use our Colab notebook:** `notebooks/AuraLock_LoRA_Benchmark_Colab.ipynb` +2. **Follow the benchmark harness:** See `src/auralock/benchmarks/` +3. **Share results:** Open an issue with your findings +4. **Compare methods:** Test against unprotected baseline and other tools + +We welcome community contributions to ground-truth validation efforts. + +--- + +## References + +- [Research Roadmap](RESEARCH_ROADMAP.md) - Planned validation timeline +- [Product Audit](PRODUCT_AUDIT.md) - Current system capabilities +- [Colab Benchmark Notebook](../notebooks/AuraLock_LoRA_Benchmark_Colab.ipynb) - GPU validation workflow +- [Benchmark Infrastructure](../src/auralock/benchmarks/) - Technical implementation + +--- + +## Disclaimer + +AuraLock is a research and learning project. The protection mechanisms are experimental and have not been validated against real-world attacks. Users should: + +- **NOT** rely solely on AuraLock for protecting valuable or commercial artwork +- **NOT** interpret proxy metrics as guarantees of protection +- **NOT** assume protection will work against all attack types +- **DO** understand this is an educational and research tool +- **DO** wait for validated results before production use +- **DO** use multiple protection layers and legal safeguards + +For production artwork protection, consult with legal professionals and consider using multiple protection methods in combination. diff --git a/src/auralock/cli.py b/src/auralock/cli.py index 1763d99..0ccd520 100644 --- a/src/auralock/cli.py +++ b/src/auralock/cli.py @@ -82,7 +82,7 @@ def _render_quality_table(report: dict[str, object]) -> Table: def _render_readability_table(report: dict[str, object]) -> Table: - table = Table(title="Protection Readability") + table = Table(title="Protection Readability (⚠️ PROXY - NOT VALIDATED)") table.add_column("Metric", style="cyan") table.add_column("Value", style="green") @@ -93,10 +93,11 @@ def _render_readability_table(report: dict[str, object]) -> Table: f"{report['robust_style_similarity']:.4f}", ) table.add_row( - "Protection score", + "Protection score (proxy)", f"{report['protection_score']:.1f}/100", ) table.add_row("Assessment", str(report["assessment"])) + table.add_row("Validation status", "❌ Not validated against real attacks") # Add warning row if present if "warning" in report: @@ -176,12 +177,12 @@ def _render_batch_table(summary: BatchProtectionSummary) -> Table: def _render_profile_summary_table( profile_summaries: dict[str, dict[str, object]], ) -> Table: - table = Table(title="Profile Summary") + table = Table(title="Profile Summary (⚠️ Protection scores are proxy metrics)") table.add_column("Profile", style="cyan") table.add_column("Images", style="green") table.add_column("Avg PSNR", style="yellow") table.add_column("Avg SSIM", style="yellow") - table.add_column("Avg Protect", style="magenta") + table.add_column("Avg Protect (proxy)", style="magenta") table.add_column("Avg Runtime", style="green") for profile, summary in profile_summaries.items(): diff --git a/src/auralock/services/protection.py b/src/auralock/services/protection.py index 750fca5..73a1e18 100644 --- a/src/auralock/services/protection.py +++ b/src/auralock/services/protection.py @@ -91,6 +91,13 @@ def to_report_dict( "perturbation_linf": self.perturbation_linf, "device": self.device, "model_name": self.model_name, + "validation_metadata": { + "is_validated": False, + "validation_status": "not_validated", + "validation_method": None, + "validation_date": None, + "notes": "Protection metrics are proxy measurements not validated against real attacks like DreamBooth or LoRA.", + }, } if output_path is not None: payload["output_path"] = output_path @@ -136,6 +143,13 @@ def to_report_dict(self) -> dict[str, object]: "failed_count": self.failed_count, "outputs": self.outputs, "failures": self.failures, + "validation_metadata": { + "is_validated": False, + "validation_status": "not_validated", + "validation_method": None, + "validation_date": None, + "notes": "Protection metrics are proxy measurements not validated against real attacks like DreamBooth or LoRA.", + }, } ) @@ -167,6 +181,13 @@ def to_report_dict(self) -> dict[str, object]: "runtime_sec": self.runtime_sec, "quality_report": self.quality_report, "protection_report": self.protection_report, + "validation_metadata": { + "is_validated": False, + "validation_status": "not_validated", + "validation_method": None, + "validation_date": None, + "notes": "Protection metrics are proxy measurements not validated against real attacks like DreamBooth or LoRA.", + }, } ) @@ -188,6 +209,13 @@ def to_report_dict(self) -> dict[str, object]: "image_count": self.image_count, "entries": [entry.to_report_dict() for entry in self.entries], "profile_summaries": self.profile_summaries, + "validation_metadata": { + "is_validated": False, + "validation_status": "not_validated", + "validation_method": None, + "validation_date": None, + "notes": "Protection metrics are proxy measurements not validated against real attacks like DreamBooth or LoRA.", + }, } )