Data-Driven Security Verification for Autonomous Debris Removal in Space

Saurav Sthapit; Gregory Epiphaniou; Carsten Maple

doi:10.1109/AERO53065.2022.9843541

Data-Driven Security Verification for Autonomous Debris Removal in Space

Saurav Sthapit, Gregory Epiphaniou, Carsten Maple

University of Warwick

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abstract

Autonomous Debris Removal allows debris in space to be collected and removed safely from the orbit. However, it relies on the integrity of the sensor data such as LiDAR to estimate the pose of the target (debris). If the sensor data is manipulated, the service vehicle may fail to grasp the target or in worse case damage the vehicle itself or nearby satellites. This paper utilises the multi-modal sensor data to verify the integrity of the sensor data to ensure safe operation of the debris removal. Using the specific domain knowledge for the Autonomous Debris Removal, we propose a computationally efficient algorithm to confirm the point cloud data has not been tampered with. Our experimental results show that significant modification of point cloud can be detected.

Original language	English
Title of host publication	2022 IEEE Aerospace Conference (AERO)
Publisher	IEEE
Pages	1-8
Number of pages	8
ISBN (Electronic)	978-1-6654-3760-8
ISBN (Print)	978-1-6654-3761-5
DOIs	https://doi.org/10.1109/AERO53065.2022.9843541
Publication status	Published - 10 Aug 2022
Externally published	Yes
Event	2022 IEEE Aerospace Conference (AERO) - Big Sky, MT, USA Duration: 5 Mar 2022 → 12 Mar 2022

Publication series

Name	IEEE Aerospace Conference proceedings
Publisher	IEEE
ISSN (Print)	1095-323X

Conference

Conference	2022 IEEE Aerospace Conference (AERO)
Period	5/03/22 → 12/03/22

Bibliographical note

Funding Information:
The work presented has been funded by Grant EP/R026092/1 (FAIR-SPACE Hub) through UK Research and Innovation (UKRI) under the Industry Strategic Challenge Fund (ISCF) for Robotics and AI Hubs in Extreme and Hazardous Environments. Authors would like to thank Dr Nikos Mavrakis, Prof. Yang Gao and the team for sharing the data from the orbital testbed.

Funding Information:
Saurav Sthapit is a Research Fellow in Cyber Systems Engineering in WMG at the University of Warwick. He received the BE degree in electronics and com- munication engineering from Tribhuvan University, Nepal, the MSc degree in embedded systems from the University of Kent, England and the PhD degree in the Institute for Digital Communica- tions, within the School of Engineering, University of Edinburgh, Scotland. His research interests include computer vision, mobile computing, cyber security, and reinforcement learning, etc Gregory Epiphaniou Currently holds a position as an Associate Professor of security engineering at the University of Warwick. His role involves bid support, applied research and publications. Part of his current research activities is for-malised around cyber effects modeling, wireless communications with the main focus on crypto-key generation, exploit-ing the time-domain physical attributes of V-V channels and cyber resilience. He led and contributed to several research projects funded by EPSRC, IUK and local authorities totalling over £4M. He currently holds a subject matter expert panel position in the Chartered Institute for Securities and Investments. He acts as a technical committee member for several scientific conferences in Information and network security and served as a key member in the development of WS5 for the formation of the UK Cybersecurity Council.

Publisher Copyright:
© 2022 IEEE.

Funding

The work presented has been funded by Grant EP/R026092/1 (FAIR-SPACE Hub) through UK Research and Innovation (UKRI) under the Industry Strategic Challenge Fund (ISCF) for Robotics and AI Hubs in Extreme and Hazardous Environments. Authors would like to thank Dr Nikos Mavrakis, Prof. Yang Gao and the team for sharing the data from the orbital testbed. Saurav Sthapit is a Research Fellow in Cyber Systems Engineering in WMG at the University of Warwick. He received the BE degree in electronics and com- munication engineering from Tribhuvan University, Nepal, the MSc degree in embedded systems from the University of Kent, England and the PhD degree in the Institute for Digital Communica- tions, within the School of Engineering, University of Edinburgh, Scotland. His research interests include computer vision, mobile computing, cyber security, and reinforcement learning, etc Gregory Epiphaniou Currently holds a position as an Associate Professor of security engineering at the University of Warwick. His role involves bid support, applied research and publications. Part of his current research activities is for-malised around cyber effects modeling, wireless communications with the main focus on crypto-key generation, exploit-ing the time-domain physical attributes of V-V channels and cyber resilience. He led and contributed to several research projects funded by EPSRC, IUK and local authorities totalling over \u00A34M. He currently holds a subject matter expert panel position in the Chartered Institute for Securities and Investments. He acts as a technical committee member for several scientific conferences in Information and network security and served as a key member in the development of WS5 for the formation of the UK Cybersecurity Council.

Funders	Funder number
UK Research and Innovation
International University of Korea
Engineering and Physical Sciences Research Council	EP/S035362/1

Keywords

Space vehicles
Point cloud compression
Satellites
Laser radar
Multimodal sensors
Conferences
Orbits

Access to Document

10.1109/AERO53065.2022.9843541

Cite this

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abstract = "Autonomous Debris Removal allows debris in space to be collected and removed safely from the orbit. However, it relies on the integrity of the sensor data such as LiDAR to estimate the pose of the target (debris). If the sensor data is manipulated, the service vehicle may fail to grasp the target or in worse case damage the vehicle itself or nearby satellites. This paper utilises the multi-modal sensor data to verify the integrity of the sensor data to ensure safe operation of the debris removal. Using the specific domain knowledge for the Autonomous Debris Removal, we propose a computationally efficient algorithm to confirm the point cloud data has not been tampered with. Our experimental results show that significant modification of point cloud can be detected.",

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Data-Driven Security Verification for Autonomous Debris Removal in Space

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

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Cite this