README.md

metadata

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:

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"])})