Update README.md

README.md

@@ -1,3 +1,55 @@
----
-license: mit
----
+# NSG Dataset (Network Security Group Logs)
+
+## License
+**MIT License**
+
+## Dataset Overview
+The **NSG Dataset** contains **500 records** of simulated **Network Security Group (NSG) logs** to analyze security threats, detect anomalies, and build AI-driven threat prediction models. It includes details on network traffic, threat levels, and response actions.
+
+## Dataset Files
+- `nsg_dataset.csv` - Contains the main dataset with 500 records.
+- `README.md` - Documentation for understanding and using the dataset.
+
+## Data Schema
+
+| Column Name      | Data Type | Description |
+|-----------------|----------|-------------|
+| `timestamp`      | `string` (YYYY-MM-DD HH:MM:SS) | Date and time of the network event |
+| `source_ip`      | `string` (IPv4) | IP address of the source device |
+| `destination_ip` | `string` (IPv4) | IP address of the target device |
+| `protocol`       | `string` | Network protocol (TCP, UDP, ICMP) |
+| `port`          | `integer` | Destination port (20 - 65535) |
+| `action`         | `string` | Whether the traffic was **Allowed** or **Denied** |
+| `threat_level`   | `string` | Severity of the security event (**Low, Medium, High, Critical**) |
+| `threat_type`    | `string` | Type of attack (**DDoS, Brute Force, SQL Injection, Port Scan, Malware**) |
+| `response_action`| `string` | Action taken (**Blocked, Alerted, Monitored, Escalated**) |
+
+## Dataset Statistics
+- **Total Records:** 500
+- **Unique Source IPs:** ~400+
+- **Threat Level Distribution:**
+  - Low (~25%)
+  - Medium (~30%)
+  - High (~25%)
+  - Critical (~20%)
+
+## Use Cases
+- **Anomaly Detection:** Identify unusual traffic patterns.
+- **Threat Intelligence:** Analyze network security trends.
+- **Machine Learning Models:** Train AI models for cyber threat prediction.
+- **Power BI Dashboards:** Visualize security logs for real-time monitoring.
+
+## How to Use the Dataset
+### **Python (Pandas) Example**
+```python
+import pandas as pd
+
+df = pd.read_csv("nsg_dataset.csv")
+print(df.head())  # Preview first 5 records
+```
+
+
+## Contact
+📧 **Email:** [email protected]  
+📍 **Location:** Bengaluru, India
+