Practical cryptographic schemes for analysing data in a privacy-preserving way.
Effectively combine cryptography with the principles of differential privacy
Besides processing statistical data in a privacy-preserving way, we also aim to enable a richer, more balanced and comprehensive approach where data analytics and cryptography go hand in hand to enable text, image and video processing.
![image01](https://harpocrates-project.eu/wp-content/uploads/2022/11/image01-1.png)
Cryptography
Cryptographic protocol based on HHE to collect data from multiple sources and compute specific functions over them, in a privacy-preserving way.
![image02](https://harpocrates-project.eu/wp-content/uploads/2022/11/image02-1.png)
Privacy
Creating a digitally blind evaluation system.
![image03](https://harpocrates-project.eu/wp-content/uploads/2022/11/image03-1.png)
AI
Federated learning and decentralized deep learning allow to process large information volume faster.
![image04](https://harpocrates-project.eu/wp-content/uploads/2022/11/image04.png)
Big Data
Use large volumes of user data to adopt, improve and fine tune services.
In a Nutshell
Availability of Big Data combined with advancements in Artificial Intelligence (AI) enable broad capabilities for both private and public actors. However, cross-organisation and cross-border data sharing in-line with GDPR is increasingly difficult, as collection of granular, multi-dimensional personal data meets improved capabilities to cross-link data sets.
HARPOCRATES leverages novel cryptographic schemes to advance the capabilities of Privacy Preserving Machine Learning (PPML) and Federated Learning (FL), thus enabling decentralised training, validation, and prediction on encrypted data. Such privacy-preserving services and secure computation enable users to both benefit from cloud-based machine intelligence and maintain control over data.
HARPOCRATES will enable digitally blind evaluation systems demonstrated in practical application scenarios, helping build fairer, democratic, and unbiased societies.
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Harpocrates team comprises a consortium of 13 members, including universities, university hospitals, SMEs and regional government administration bodies.
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Different countries including United Kingdom, Finland, Sweden, Ireland, Serbia, Germany, Spain, Italy and France.
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Coordinator of the project is Tampere University, Finland. Project kickoff is in October and its planned to last until October 2025.
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Harpocrates project is financed by EU Commission with the total budget of 4 mil EU and £0.34 mil by UKRI.
Our latest news to stay in focus of how we do it
![what-if](https://harpocrates-project.eu/wp-content/uploads/2024/09/what-if.jpg)
![interview-ricardo](https://harpocrates-project.eu/wp-content/uploads/2024/05/interview-ricardo.png)
News
Exploring Cybersecurity Innovations: An Interview with Ricardo Gonçalves, Harpocrates Project Focus Group Member
![NEWPOST](https://harpocrates-project.eu/wp-content/uploads/2024/04/NEWPOST.jpg)
![GuardML-publication-featured](https://harpocrates-project.eu/wp-content/uploads/2024/03/GuardML-publication-featured.jpg)
News
GuardML: Efficient Privacy-Preserving Machine Learning – A Publication from Tampere University
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