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forensics_mc_generator
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---
title: Digital Forensics Model Card Generator
emoji: 🔬
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.9.1
app_file: app.py
pinned: false
license: apache-2.0

---

# 🔬 Digital Forensics Model Card Generator

A standardized tool for creating model cards for digital forensics AI/ML systems.

## Overview

This generator implements a structured framework for documenting digital forensics models based on:

1. **Di Maio, P.** (2024). Towards Open Standards for Systemic Complexity in Digital Forensics. https://papers.cool/arxiv/2512.12970

2. **Hargreaves, C., Nelson, A., & Casey, E.** (2024). An abstract model for digital forensic analysis tools—A foundation for systematic error mitigation analysis. *Forensic Science International: Digital Investigation*, 48.

## Features

### Three-Section Structure

1. **Metadata** - Core identification and classification information
2. **Top Level Elements (DF MC 0)** - Conceptual framework from Figure 6
3. **Data & Processes (DF MC 1)** - Analytical workflow from Figure 7

### Controlled Vocabularies

The generator includes standardized taxonomies for:
- Digital forensics classification types
- Reasoning methodologies (deductive, inductive, abductive, retroductive)
- AI bias types and causes
- Error types and causes

### Output Formats

- **JSON** - Structured, machine-readable format
- **Markdown README** - Human-readable documentation with proper citations

## How to Use

1. **Fill in Metadata** - Provide identifier, version, owner, and context
2. **Select Top Level Elements** - Check applicable items and describe
3. **Select Data & Processes** - Document your analytical workflow
4. **Generate** - Download both JSON and Markdown files

## Model Card Components

### Metadata Fields

- **MMCID** - Model Card Identifier (Format: DF-MC-YYYY-NNN)
- **MCV** - Version
- **DF-MCO** - Owner
- **DF-MCUse** - Usage context (standalone/integrated)
- **DF-MC CS** - Case statement
- **DF-MC H** - Hypothesis
- **DF-MC C** - Classification (multi-select, max 3)
- **DF-MC TR** - Type of reasoning (multi-select, max 3)
- **DF-MC B** - Bias (multi-select, max 3)
- **DF-MC CB** - Cause of bias (multi-select, max 3)
- **DF-MC E** - Error description
- **DF-MC CE** - Cause of error (multi-select, max 3)
- **DF-MC Ln** - Layer/stage identifier

### Top Level Elements (Figure 6)

15 conceptual elements including:
- Type of Reasoning
- Algorithm
- Inference
- Classification
- Evaluation
- Tool
- Bias/Debiasing
- And more...

### Data & Processes (Figure 7)

19 analytical workflow elements including:
- Event/Data
- Parse Raw Data
- File System Processing
- File Hashing
- Timeline Analysis
- Geolocation
- AI-Based Content Flagging
- And more...

## Technical Details

- **Framework:** Gradio 4.0+
- **Language:** Python 3.9+
- **License:** Apache 2.0
- **Version:** 1.0.0

## Citation

If you use this generator in your research or practice, please cite:

```bibtex
@misc{dfmodelcardgenerator2024,
  title={Digital Forensics Model Card Generator},
  author={Di Maio, Paola},
  year={2024},
  howpublished={\url{https://huggingface.co/spaces/forensic-model-card-generator}},
  note={Version 1.0.0}
}
```

## Contributing

Feedback and contributions are welcome! Please open an issue or submit a pull request.

## License

MIT  - See LICENSE for details

## Contact

For questions or collaboration opportunities, please contact the repository maintainer.

---

**Note:** This is version 1.0.0 of the generator. All fields are optional in this initial release to allow for flexible adoption and evaluation.