README.md

---
language: [fa]
license: other
multilingual: false
pretty_name: encrypted_legal_dataset
task_categories: [other]
task_ids: []
source_datasets: []
---

# ara_v4

**ara_v4** is a dataset where the `text` column has been encrypted with **AES-GCM (AES-256)** 
to preserve privacy while still allowing distribution.

## Dataset Description

- **Columns**:
  - `score`: floating-point metadata value
  - `text`: Base64-encoded string containing AES-GCM encrypted text
- **Encryption**:
  - AES-256 in GCM mode


## Usage

You can load the dataset using the 🤗 Datasets library:

```python
import base64
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
from datasets import load_dataset

# 🔑 Replace this with the Base64 key provided securely
key_b64 = "PASTE-YOUR-KEY-HERE"
key = base64.b64decode(key_b64)
aesgcm = AESGCM(key)

def decrypt(token: str) -> str:
    data = base64.b64decode(token.encode())
    nonce, ciphertext = data[:12], data[12:]
    return aesgcm.decrypt(nonce, ciphertext, None).decode()

# Load dataset
dataset = load_dataset("QomSSLab/ara_v4")

# Decrypt rows
dataset = dataset.map(lambda x: {"text": decrypt(x["text"])})
```