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CORDIS

Secure Hardware and Software for AI systems

Objective

SHASAI targets the HW/SW security and AI-based high risk systems intersection, aiming to enhance the security, resilience, automated testing, and continuous assessment of AI systems. The rising interest in these systems makes them attractive targets for threat actors due to their complexity and valuable data. Ensuring the security of AI systems involves safeguarding AI models, datasets, dependencies, and securing the underlying HW/SW infrastructure.
SHASAI takes a holistic approach of AI system security throughout their lifecycle stages. At requirement definition, SHASAI provides an enhanced risk assessment methodology for secure and safe AI. At design, SHASAI will propose secure and safe design patterns at SW and HW level to achieve trustworthy AI systems. During implementation, SHASAI provides tooling for a secure supply chain of the system by analyzing vulnerabilities in SW / HW dependencies, detecting poisoned data and backdoors in pretrained models, scanning for software vulnerabilities, hardening hardware platforms, and safeguarding intellectual property. At evaluation, SHASAI offers a virtual testing platform with automated attack and defense test suites to assess security against AI and infrastructure-specific threats. In operation, AI-enhanced security services continuously monitor the system, detect anomalies, and mitigate attacks using AI firewalls and attestation methods, ensuring availability and integrity.
The feasibility of SHASAI methods and tools will be demonstrated in 3 real scenarios: 1. Agrifood industry: Cutting machines. 2. Health: Eye-tracking systems in augmentative and alternative communication. 3. Automotive: Tele-operated last mile delivery vehicle. Their heterogeneity and complementarity maximize the transferability of solutions.
SHASAI will contribute to scientific, techno-economic, and societal impacts as it aligns with the CRA, EU AI Act, NIS2 and CSA, sharing and commercializing methods and tools to ensure trustworthy AI components.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-IA - HORIZON Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-CL3-2024-CS-01

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Coordinator

IKERLAN S. COOP
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 976 077,00
Address
P JOSE MARIA ARIZMENDIARRIETA 2
20500 MONDRAGON
Spain

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Region
Noreste País Vasco Gipuzkoa
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Participants (15)

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