ROSIDS23: Network intrusion detection dataset for robot operating system


Değirmenci E.

DATA IN BRIEF, vol.51, pp.109739, 2023 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51
  • Publication Date: 2023
  • Doi Number: 10.1016/j.dib.2023.109739
  • Journal Name: DATA IN BRIEF
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, BIOSIS, CAB Abstracts, Directory of Open Access Journals
  • Page Numbers: pp.109739
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

The data described herein pertains to the Robotic Systems Security domain. This data in brief presents the attributes of the ROSIDS23 dataset and its collection process in detail. This dataset comprises Robot Operating System (ROS)based cyber-attacks to address the emerging need in high fidelity data for robotic system security research. The data was gathered from the IFARLab-DIH environment. IFARLab-DIH is a robotic and factory-level laboratory that includes a ROSbased network and is used to conduct studies up to TRL 5 on robotic systems. ROSIDS23 dataset contains benign and various attack traffic collected from the ROS middleware using the tcpdump network protocol analyser. Then the eighty-two traffic features were extracted from the captured pcap files and converted into CSV format using the CICFlowMeter tool. This dataset can serve as a valuable resource for developing and improving security countermeasures in robotic systems and can help the evolution of resilient robotics infrastructure. (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )