Update README.md

README.md

@@ -1,11 +1,38 @@
----
-license: cc-by-nc-4.0
-task_categories:
-- text-classification
-language:
-- en
-tags:
-- URL-Classification
-size_categories:
-- 100M<n<1B
----
+# DeepURLBench
+
+**DeepURLBench** is a large-scale benchmark dataset for real-world URL classification, developed by Deep Instinct's research team.
+
+## Dataset Overview
+
+The dataset includes two subsets in Parquet format:
+
+### 🟢 `urls_with_dns`
+
+Contains additional DNS resolution data:
+
+- `url`: The URL being analyzed.
+- `first_seen`: The timestamp when the URL was first observed.
+- `TTL` (Time to Live): DNS TTL value.
+- `label`: The classification label (`malware`, `phishing`, or `benign`).
+- `ip_address`: List of resolved IP addresses.
+
+### 🔵 `urls_without_dns`
+
+Contains only the core metadata:
+
+- `url`: The URL being analyzed.
+- `first_seen`: The timestamp when the URL was first observed.
+- `label`: The classification label (`malware`, `phishing`, or `benign`).
+
+## How to Load
+
+You can load the dataset using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load the subset with DNS data
+ds_dns = load_dataset("DeepInstinct/DeepURLBench", "with_dns")
+
+# Load the subset without DNS data
+ds_no_dns = load_dataset("DeepInstinct/DeepURLBench", "without_dns")