The title of this Special Interest Group is Secure, Accountable and Efficient Intelligent Networked Systems (SANE).
The SANE group brings together researchers and industry experts to address emerging security, privacy, and accountability challenges in next-generation intelligent networked systems. We increasingly live through networks – from the Internet of Things and cyber-physical systems to smart digital twins and large-scale critical infrastructures. These domains operate within complex, interconnected environments that, with the rapid advancement of frontier AI, are evolving into intelligent ecosystems where AI agents and models continuously exchange, interpret, and act upon data.
While this transformation unlocks unprecedented levels of autonomy, adaptability, and optimisation, it simultaneously raises critical questions about what information is shared, how it is protected, and how accountability and trust can be maintained across these interactions. The SANE group focuses on several interrelated research themes that address these key questions.
Key aims
SANE aims to establish a sustained, cross-institutional research and collaboration agenda structured around the proposed research themes, supporting the development of conceptual frameworks and architectures, as well as the production of community outputs such as research publications and grant proposals.
SANE research themes include, but are not limited to:
Cross-Layer Security and Resilience
Analysing interactions across network and architectural layers in AI-enabled systems to identify security and privacy risks, and developing architectural approaches to secure communication in large-scale, heterogeneous networks.
Privacy-Preserving Intelligence and Data Minimisation
Designing lifecycle-aware strategies for protecting user and system data, including selective data sharing and decentralised or federated AI approaches that preserve privacy without sacrificing performance.
Accountability and Transparency
Developing principles and mechanisms that enable transparent, traceable, and verifiable communication and decision-making in AI-enabled networked systems to strengthen trust and oversight.
Efficiency and Adaptability
Balancing security, privacy, and accountability with resource efficiency through lightweight models, in-network intelligence, and adaptive learning strategies that maintain robustness and resilience.
Main contacts
Dr. Vadim Safronov
Research Associate, Department of Computer Science and Junior Research Fellow, Kellogg College, University of Oxford.
Dr Nicholas Allott
CEO and Founder,
NquiringMinds Ltd.
Prof. Richard Mortier
Professor of Computing & Human-Data Interaction in the Department of Computer Science and President of Christ’s College, University of Cambridge.
Upcoming events
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