The results obtained in our projects and solutions related to Security and Privacy endorse our expertise in this area. Throughout these years we have developed secure solutions adapted to the specific needs of our clients and applicable in different areas.
These technologies follow the principle of security and privacy by design, i.e. we take into account aspects such as confidentiality, privacy and integrity of information.Thanks to the anonymization of data, our solutions allow us to analyze and process information while preserving the privacy and identity of users.
Today we can talk about the application in production processes of the Internet of Things (Internet of Things – IoT) and Embedded Systems (Embedded Systems) thanks to the work done in Cyberphysical Systems (CPS). With these advances we achieve the integration of computing systems, data networks and physical processes in sectors such as industry, agribusiness or fisheries.
Our experience in identity and privacy technologies makes us a technological center of reference in this field. We have researched and developed solutions related to security and privacy with multiple applications in areas ranging from public administration to the banking sector. Through different technologies and techniques researched and developed by our team we have achieved the optimal balance between privacy and data utility. In addition, we improve the control of... Continue reading
We protect access to information and critical systems from attacks and at the same time guarantee the availability of services. To this end, we take advantage of the possibilities of data analysis of different types, artificial intelligence and deep learning. This combination allows us to offer innovative cybersecurity solutions to protect the confidentiality of critical business information.
Confidential computing is a line with great potential for development today and in the near future for various sectors and scenarios. In Gradiant we work specifically on aspects such as secure federated learning, attribute-based encryption and machine learning while preserving security and privacy.
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