SAIMAS – Secure AI within Marine Autonomy Systems
Improving the cyber resilience of AI and marine autonomy systems
Title: SAIMAS – Secure AI within Marine Autonomy Systems
Funding body:
Funding period: December 2022 – December 2024
°µÍø½âÃÜ PI:
Dr Kimberly Tam
°µÍø½âÃÜ 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 °µÍø½âÃÜ, AI is applied in marine science to enhance our understanding of biodiversity and the marine environment.
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.
Our people
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![Dr Kimberly Tam Associate Professor in Cybersecurity]( "Dr Kimberly Tam")
Dr Kimberly Tam
Associate Professor in Cybersecurity
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![Mr Aaron Barrett Technical Specialist - Marine Autonomy and Clean Maritime Systems]( "Mr Aaron Barrett")
Mr Aaron Barrett
Technical Specialist - Marine Autonomy and Clean Maritime Systems
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