Services
Confidential AI
- Achieving end-to-end security and privacy assurance of AI systems
- Privacy-preserving federated machine learning
- Trustworthy analysis and prediction systems in a privacy-preserving manner
AI in Defence
- AI-based configurable applications that can be integrated into defence sector systems
- Monitoring tools for information warfare
- Interoperable AI-based subsystems
AI engineering
- Large Language Model (LLM) setup
- Trustworthy Retrieval-Augmented Generation
- Tools used in the Defence industry
Consultancy
- Risk assessment
- Guidance on how to ensure cyber security and safety of AI implementations
- IT compliance
- Adding AI to technology roadmaps
References
Study and training videos on cyber security aspects of AI systems for the Estonian Information System Authority (RIA)
- Analysis of the risks of artificial intelligence (AI) technology and how to mitigate them.
- Supporting the implementation of the technology by providing guidance on how to ensure cybersecurity, legal compliance and safety for society.
Project EUCINF European Cyber and Information warfare toolbox, funded by European Commission
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Creating a library of adaptable software components that can be seamlessly integrated into cyber and information warfare systems.
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Processing audio, video, image and text data, to interlink and contextualise information and to support the detection and remediation of information warfare activities.
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Developing AI-enabled components for the collection, enrichment, categorisation and clustering of information as well as the detection of propaganda, mis- and disinformation.
Project STORE Shared database for Optronics image Recognition and Evaluation, funded by European Commission
- AI-based image recognition system to support faster detection and decision-making in defence sector.
- Constructing a shared database of annotated defence images to train AI systems.
- Developing methods to leverage machine learning with classified data.
Project PAI-MACHINE Synthesis of machine-optimized cryptographic protocols with applications in secure machine learning systems, funded by Office of Naval Research
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Developing secure machine learning tools, new protocols using post-quantum cryptography, code generation integrating the abilities of up-and-coming hardware architectures.
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Generalizing and scaling up the ability to synthesize efficient code for running cryptographic protocols from scalar operations to full algorithms.
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Implementing cryptographically secure machine learning protocols.
Project EXAI Estonian Centre of Excellence in Artificial Intelligence, funded by the Estonian Ministry of Education and Research
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Increasing AI capabilities in key Estonian sectors, including e-governance, healthcare, business process management, and cybersecurity.
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Leveraging foundation models in building efficient and trustworthy analysis and prediction systems.
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Implementing control mechanisms and guardrails to ensure that the advanced AI systems follow their specification.
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Adapting and enhancing AI systems for improved performance in targeted application contexts.
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Achieving end- to-end security and privacy assurance of AI systems.
Project MINERVA, funded by European Space Agency (ESA)
- Machine learning algorithms for increasing cyber situational awareness, to support threat and vulnerability management.
- Comprehend complex local and external network activity and identify problem areas and suspicious behaviour.
- Reducing the workload of cybersecurity specialist, IT administrator or an auditing security analyst.
- Integrated into the ESA cybersecurity toolkit.
Building secure AI applications
Dan Bogdanov and Liina Kamm from Cybernetica AS talk about the security & privacy aspects surrounding the use of Artificial Intelligence.
