metadata
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
import pandas as pd
df = pd.read_csv("nsg_dataset.csv")
print(df.head()) # Preview first 5 records