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KIProtect: The security layer for data science and artificial intelligence

Descripción del proyecto

Métodos nuevos para mejorar la seguridad de datos sensibles

La ciencia de datos, el aprendizaje automático y la inteligencia artificial son campos en rápido desarrollo. Con todo, lo datos a emplear y analizar en estos campos suelen ser sensibles y protegerlos constituye un reto complejo. El objetivo del proyecto KIProtect, financiado con fondos europeos, es abordar este reto con un método totalmente nuevo e innovador destinado a la protección y seguridad de los datos que se adapta específicamente a los datos masivos y la inteligencia artificial. El proyecto proporcionará un método novedoso de seudonimización de datos basado en técnicas criptográficas y estadísticas de transformación de datos, lo que permitirá a los clientes trabajar fácilmente con datos sensibles y compartirlos, al tiempo que se garantiza el cumplimiento normativo y la seguridad.

Objetivo

The importance of data science, machine learning and artificial intelligence is increasing rapidly. Concepts like smart home, smart cities, connected car, Internet of Things (IoT) and industry 4.0 all require large amounts of data that need to be collected, stored and analyzed. To remain relevant and competitive, companies and public organizations alike need to follow this trend. However, the data they want to use and analyze is often sensitive, and protecting it is a difficult challenge.

KIProtect solves this challenge with an entirely new, innovative approach for data security and data protection that is specifically tailored to big data and artificial intelligence: We provide a novel data pseudonymization approach based on modern cryptographic and statistical data transformation methods. This allows our customers to easily work with and share sensitive data while ensuring compliance and security, enabling them to build data-driven business processes on top of secure data streams. Our technology is currently being tested in several proof of concept (PoC) projects and demonstrably works. It is unique in that it can reliably protect high-dimensional data (e.g. images or time series) while retaining most of the data utility. We therefore have a strong USP and are currently pursuing patent protection for our core algorithm as well, which will grant us a very strong position in the large and fast-growing data security market. We plan to use the H2020 funding to prove the applicability of our approach for specific industries and to develop PoC solutions that enable companies to build secure and robust data processing systems for specific use cases. We have realized a first prototype implementation of our methods as an API and are already working with our first pilot customers to validate our business plan. The European data security market has a volume of more than 1 BN € and grows at 15 % per year. We are confident that we can become a technology leader in it.

Convocatoria de propuestas

H2020-EIC-SMEInst-2018-2020

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-SMEInst-2018-2020-1

Régimen de financiación

SME-1 - SME instrument phase 1

Coordinador

7SCIENTISTS GMBH
Aportación neta de la UEn
€ 50 000,00
Dirección
SACHSISCHE STR. 26
10707 BERLIN
Alemania

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Pyme

Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.

Región
Berlin Berlin Berlin
Tipo de actividad
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Enlaces
Coste total
€ 71 429,00

Participantes (1)