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---
title: NSG Dataset (Network Security Group Logs)
license: mit
datasets:
- nsg_dataset
tags:
- cybersecurity
- network-security
- anomaly-detection
- machine-learning
---
# 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
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