Community Research and Development Information Service - CORDIS

H2020

BigDecisions Report Summary

Project ID: 728567

Periodic Reporting for period 1 - BigDecisions (BigDecisions – Data-driven decision making with cryptographic confidentiality)

Reporting period: 2016-06-01 to 2016-11-30

Summary of the context and overall objectives of the project

Over the last ten years, Cybernetica’s R&D team has developed privacy-preserving technologies under the Sharemind trademark. Sharemind lets you extract value from the confidential data of several other parties so that no secrets are revealed to anyone and interested parties can remotely control processing.

Thus, Sharemind enables better decisions for all organisations by providing provable end-to-end privacy for data. Sharemind reduces costs of complying with data protection laws and enables use cases, which are impossible without our technology.

Sharemind builds on Cybernetica’s breakthroughs in secure computing R&D and significantly improves the privacy guarantees of apps and services, enabling applications that were impossible before. Our engineering work has given us an edge in cryptographic and hardware-supported secure computing. Our prototyping and commercialisation efforts have been successful, but we want to respond to the growing need for privacy technologies.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The goal of this feasibility study was to set a clear focus for our business and technology development, to identify key markets, customer groups to approach, partners needed, size of funding required and potential sources of funding.

We performed the following tasks during the project.
1) We defined the Sharemind product scope, the customer pain and a value proposition.
2) We identified target markets and business models.
3) We identified the technology-market gap and improvements needed to Sharemind.
4) We assessed legal risks and reviewed controls to mitigate them.
5) We formulated a market entry strategy.
6) We made financial projections to evaluate the economic feasibility of the approach.

We formed a business plan with a motivating revenue potential, including international expansion. We also calculated an estimate for the first rounds of investments.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Before this feasibility study, the Sharemind team had successfully performed a number of both commercial and R&D projects for a range of customers. However, we lacked a business focus and a way forward. In this project, we conducted a market study and identified the key markets to focus our work on.

We understood that the key demand drivers are the introduction of the General Data Protection Regulation and signing of the EU-US Privacy Shield agreement. Additionally, Sharemind is an enabler for the European Digital Single Market and global cross-border digital services and data sharing. Currently, no other technology provides privacy-preserving data analysis with the same security guarantees as Sharemind. European Data Protection specialists and legal experts have stated that, with the correct processes, goals of Privacy by Design in Article 25 of the General Data Protection Regulation can be met with Sharemind. Even more, if the aggregation results do not contain personal data, using Sharemind on private inputs means that no personal data is processed in the meaning of the law.

The feasibility study helped us significantly improve business and technology development and confirmed the economic viability of Sharemind. Cybernetica will now scale up its business activities related to Sharemind and thiswill lead to the better availability of privacy technologies for both European and international stakeholders. We see two main impact areas. First, there will be new disruptive business models that were previously impossible due to immature privacy technologies. Companies and governments can extract value from previously unused data. Second, existing services and business models will become more privacy-preserving, reducing cost and improving compliance and avoiding large privacy compromises in all organisations.

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