SAIMAS – Secure AI within Marine Autonomy Systems

Improving the cyber resilience of AI and marine autonomy systems
Harbour with graphical overlay
Title: SAIMAS – Secure AI within Marine Autonomy Systems
Funding body:
Funding period: December 2022 – December 2024
¶¶Òõ¶ÌÊÓƵ PI: Dr Kimberly Tam
¶¶Òõ¶ÌÊÓƵ staff: Mathew Walter , Mr Aaron Barrett
This work was supported by the Turing’s Defence and Security programme through a partnership with the UK government in accordance with the framework agreement between GCHQ and the Alan Turing Institute.
Artificial intelligence (AI) and machine learning (ML) are increasingly being utilised in ocean-related activities across science, industry, and defence sectors.
For instance, navy minesweepers are leveraging AI to minimise risks to personnel while accelerating the detection and neutralisation of mines. Additionally, the United States Department of Defence has announced initiatives to use AI for detecting and combating illegal fishing as part of its new defence innovations.
At the ¶¶Òõ¶ÌÊÓƵ, AI is applied in marine science to enhance our understanding of biodiversity and the marine environment.
SAIMAS
Woman sat at computer in cyber-SHIP lab conducting cyber security measures on a screen that says 'virus alert'
Cyber security concept - image courtesy of Getty Images
 

Project objectives

This project aims to enhance the cyber resilience of AI in marine autonomous systems by recommending best practices throughout the lifecycle of marine AI – from development and training to deployment. The project also explores the use of sensor fusion as a means of bolstering cyber resilience against attacks targeting AI systems. Furthermore, this work includes proposing extensions to the guidelines for developing secure AI.
 

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