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Update documentation for new steganography and hash verification modules
Co-authored-by: CodeRafay <154733908+CodeRafay@users.noreply.github.com>
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CHANGELOG.md

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- Machine learning-based forgery detection
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- Real-time video frame analysis
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- Advanced CMFD with SIFT/SURF
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- Blockchain-based image authentication
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---
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## [1.1.0] - 2025-12-12
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### Added - Information Security Modules
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- **🔐 Steganography Detection Module**:
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- LSB (Least Significant Bit) statistical analysis
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- Chi-square testing for randomness detection
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- Per-channel (RGB) probability scoring
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- Block-based spatial analysis with heatmaps
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- Visual analysis maps highlighting suspicious regions
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- Batch processing capability
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- Comprehensive interpretation guidelines
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- Educational documentation (Descriptions/Steganography.md)
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- Full test coverage (tests/test_steganography_detection.py)
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- **🔑 Cryptographic Hash Verification Module**:
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- Perceptual hashing (pHash, aHash, dHash, wHash) using imagehash
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- SHA-256 cryptographic hashing for exact matching
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- JSON-based blockchain simulation for provenance tracking
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- Modification history with timestamps
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- Authenticity scoring (0-100 scale)
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- Legal chain of custody assessment
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- Database management (import/export functionality)
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- Hamming distance calculation for similarity matching
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- Educational documentation (Descriptions/Hash_Verification.md)
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- Full test coverage (tests/test_hash_verification.py)
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- **UI Integration**:
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- Two new tabs in Streamlit interface (🔐 Steganography, 🔑 Hash Verify)
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- Interactive analysis workflows with progress indicators
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- Visual heatmaps and detailed results display
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- Database management interface for hash verification
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- Consistent error handling and user feedback
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- Educational tooltips and interpretation guides
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### Changed
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- Updated tab count from 12 to 14 in main application
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- Enhanced TECHNIQUES dictionary with new modules
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- Updated README.md with new feature descriptions
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- Expanded project structure documentation
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### Dependencies
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- Added `imagehash` for perceptual hashing (pip install imagehash)
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- Confirmed `scipy` already present for statistical tests
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### Testing
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- 14 passing tests for steganography detection (98% coverage)
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- 18 passing tests for hash verification (84% coverage)
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- Edge case handling for invalid inputs and small images
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---
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- **Web-Based Interface**:
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- Streamlit-powered interactive GUI
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- 12-tab navigation system
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- 12-tab navigation system (now 14 tabs)
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- Real-time parameter adjustment
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- Image upload and preview
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- Dark theme with neon green accents

README.md

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[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
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[![Streamlit](https://img.shields.io/badge/streamlit-1.28+-red.svg)](https://streamlit.io)
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**Veritas** is a comprehensive web-based digital forensics tool for detecting image forgeries and manipulations using 11 advanced analysis techniques.
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**Veritas** is a comprehensive web-based digital forensics tool for detecting image forgeries and manipulations using 13 advanced analysis techniques.
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## 🎯 Features
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9. **Frequency Domain Analysis** - FFT/DCT-based tampering detection
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10. **Deepfake Detection** - GAN artifact classification
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11. **Resampling Detection** - Image resizing and interpolation artifacts
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12. **Steganography Detection** - LSB statistical analysis for hidden data detection
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13. **Hash Verification** - Cryptographic provenance tracking and authentication
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### Information Security Features
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- **🔐 LSB Steganography Detection** - Chi-square testing for hidden data in Least Significant Bits
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- **🔑 Blockchain-Based Provenance** - Cryptographic and perceptual hash verification
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- **⚖️ Legal Chain of Custody** - Track image modifications with timestamps
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- **🔒 SHA-256 Integrity** - Exact file matching for evidence verification
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- **👁️ Perceptual Hashing** - Detect similar images despite minor modifications
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### Additional Features
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- **Technique Descriptions** - Built-in educational guides for each analysis method
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- **Default Sample Image** - Preloaded image for instant testing without upload
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- **Web-based Interface** - No installation required, runs in browser
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- **Dark Theme** - Professional forensic UI with neon accents
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- **12 Analysis Tabs** - Organized, intuitive workflow
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- **14 Analysis Tabs** - Organized, intuitive workflow
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- **Human-Readable Results** - Authenticity scoring (0-100) and risk levels
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- **Real-time Processing** - Instant visual feedback
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- **Cloud Deployment Ready** - Deploy to Streamlit Cloud in minutes
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│ ├── frequency_analysis.py # FFT/DCT analysis
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│ ├── deepfake_detector.py # GAN detection
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│ ├── resampling_detector.py # Resampling detection
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│ ├── steganography_detection.py # LSB steganography detection
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│ ├── hash_verification.py # Cryptographic provenance
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│ └── util.py # Helper functions
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├── Descriptions/ # Technique education module (NEW)
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│ ├── ELA.md # ELA guide
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│ ├── Metadata.md # Metadata guide
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│ ├── Steganography.md # Steganography detection guide
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│ ├── Hash_Verification.md # Hash verification guide
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│ ├── Histogram.md # Histogram guide
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│ ├── Noise_Ghost.md # Noise/Ghost guide
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│ ├── Quantization.md # Quantization guide

TECHNIQUE_DESCRIPTIONS_USER_GUIDE.md

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[💾 Quantization] [🔄 CMFD]
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[📡 PRNU] [📈 Frequency]
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[😁 Deepfake] [🔀 Resampling]
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[🔐 Steganography] [🔑 Hash Verify]
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```
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## 🔍 Available Techniques
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- **Analogy**: Like tree rings showing growth history
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- **File size**: 8.8 KB | **Content**: Scaling factor detection
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### 11. 🔐 **Steganography Detection**
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- **What it shows**: Hidden data in Least Significant Bits (LSB)
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- **Analogy**: Like invisible ink detection using special tests
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- **File size**: 6.1 KB | **Content**: Statistical analysis guide
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### 12. 🔑 **Hash Verification**
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- **What it shows**: Cryptographic provenance and authenticity
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- **Analogy**: Like DNA testing for digital files
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- **File size**: 10.0 KB | **Content**: Blockchain tracking guide
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## 📖 What Each Description Contains
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### Standard Sections:
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| Metric | Value |
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| -------------------------- | ----------------------------- |
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| **Total Techniques** | 10 |
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| **Total Content** | ~75 KB |
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| **Total Lines** | ~1,500+ |
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| **Average per Technique** | ~7.5 KB, 150 lines |
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| **Total Techniques** | 12 |
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| **Total Content** | ~91 KB |
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| **Total Lines** | ~1,800+ |
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| **Average per Technique** | ~7.6 KB, 150 lines |
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| **Shortest Description** | ELA (4 KB, 109 lines) |
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| **Longest Description** | Deepfake (9.6 KB, 200+ lines) |
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| **Longest Description** | Hash Verification (10 KB) |
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| **Non-technical Language** | 100% (no jargon) |
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| **Real-world Examples** | 30+ included |
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| **Visual Analogies** | 10 (one per technique) |
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| **Real-world Examples** | 35+ included |
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| **Visual Analogies** | 12 (one per technique) |
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## 🔧 Technical Details
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