Citation

Zailan, Nawfal Syafi’ and Ong, Lee Yeng and Lim, Heng Siong (2026) NAVBOT25: Dataset for ROS-based autonomous robot navigation. Data in Brief, 65. p. 112617. ISSN 2352-3409

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Abstract

This paper presents NAVBOT25, a labelled dataset aimed at strengthening the overall security of autonomous robots against network-based cyber threats within the Robot Operating System (ROS) platform. NAVBOT25 offers a comprehensive, labelled dataset that captures both normal operational behaviour and a variety of attack scenarios relevant to ROS-based systems. This dataset was generated by deploying a TurtleBot3 running ROS Noetic in controlled laboratory setting, where real-world attack vectors were executed — including SSH brute-force attempts, reverse shells, port scans, and ROS-specific attacks such as unauthorized publishing actions and topic flooding. Network traffic was captured using tcpdump, and 83 flow-level features were extracted using CICFlowMeter, resulting in a series of CSV files. Designed to support the development of AI-assisted intrusion detection systems, NAVBOT25 addresses existing gaps in robotic cybersecurity research by providing a richer and more diverse dataset for evaluating threat detection in networked robotic systems.

Item Type:	Article
Uncontrolled Keywords:	Robot operating system (ROS), cybersecurity
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET) Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Apr 2026 07:39
Last Modified:	06 Apr 2026 07:58
URII:	http://shdl.mmu.edu.my/id/eprint/15672

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