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Graph metadata dataset from grouped botnet network activities.

Muhammad Aidiel Rachman Putra¹, Tohari Ahmad¹, Royyana Muslim Ijtihadie¹

¹Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.

|November 5, 2025

Summary

This summary is machine-generated.

Detecting botnets is challenging due to their distributed nature. This study introduces a novel dataset for group-level botnet detection, analyzing network traffic as graphs to identify coordinated malicious activities.

Keywords:

Botnet detection Communication metadata Cyber security Graph-based representation Grouped botnet activities In-Degree and Out-Degree Dataset National security Network traffic dataset

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Area of Science:

Computer Science
Cybersecurity
Network Security

Background:

Botnets pose significant threats due to their distributed structure and synchronized attacks.
Existing detection methods often struggle with the complexity of group-based botnet activities.

Purpose of the Study:

To develop a novel dataset for group-level botnet detection.
To provide a realistic, graph-based perspective on botnet behavior for research and development.

Main Methods:

Extracted network activity from CTU-13, NCC, and NCC-2 botnet datasets.
Grouped traffic by host and time, representing it as graphs (hosts as vertices, communications as edges).
Derived metadata features, including in-degree and out-degree, to capture incoming and outgoing activity volumes.

Main Results:

Generated a dataset with millions of normal and botnet activity group instances based on in-degree and out-degree analyses.
The dataset offers a unique group-oriented perspective on botnet behavior.
Identified >57k botnet activity groups via in-degree and >384k via out-degree analysis across multiple datasets.

Conclusions:

The developed dataset serves as a valuable benchmark for group-based botnet detection models.
It supports research in graph-based machine learning and anomaly detection for cybersecurity.
Limitations include potential masking of individual host behaviors and loss of detailed information like ports.