Privacy protected federated machine learning
How to share data sets securely and obtain or facilitate meaningful insights
Leveraging Cross Pollinated Data
EyA has developed a platform to embrace rich data relationships using the template engine and various levels of asset associations / hierarchy. With this in mind, EyA has now developed EyA Envision, a full data analytics platform to enable organisations and people to “loan out” suitable data for research and development purposes, all whilst preserving data privacy and compliance with GDPR and other PII regulations.
As EyA is an enriched platform for not only the normal supply chain, but also a semantics delivered asset lifecycle and ownership solution, the data owned by all participants organically grows during the entire lifecycle of assets crossing industry boundaries due to EyA’s industry agnostic framework.
Many challenges
Many challenges, many unsuccessful attempts at solutions
Business leaders are looking for ways to cross-pollinate true, holistic insights, unconstrained by current industry-sector, single-organisation, division, function or team data silos.
Technologies have in some ways exacerbated this, constrained by a focus on data capture and following arbitrary workflows and adherence to regulatory and audit requirements. Less focus has been on facilitating business insights — that is: how do you get meaningful insights from all that captured data.
What’s more, small-to-medium sized enterprises wish to participate in contributing to a rich tapestry of business intelligence, but are shut out right now. Larger players have typically participated as they are able to overcome these cost barriers.
Even the organisations who have successfully managed to curate data-lakes still grapple with the dual challenges of managing data privacy and the data literacy required to derive valuable intelligence from data.
Data Exchange Platform
Delivering more than the promise of data intelligence
Data Lenders and Data Borrowers are brought together to exchange data. Any Data Lender or Data Borrower is able to participate, whether individual, small enterprise or large enterprise. Data Borrowers are able to access rich data that has been cross-pollinated from the plethora of participating Data Lenders.
Pre Analysed and Classified Data
Data Lenders apply to participate within the exchange programme. With granular levels of privacy marked on asset data, they can preserve all intellectual property and sensitive information, whilst proffering lower privacy graded data. EyA executes grading and classification AI within enclaves to ensure that data being submitted is of high grade and will benefit those wishing to hire within the data exchange.
Analysis as a Service
Once an organisation has completed the hiring of data from a person/s or company/s, their pre agreed algorithms are executed in enclaves within Conclave and the results returned. At no given time are they permitted to see any data and no private data is returned in the data set of results. The data hired is never seen by the organisation during any part of the process.
Conclave Confidential Computing
Harnessing the power of Confidential Computing - Conclave from R3
EyA uses Intel Software Guard Extensions (Intel SGX) technology to ensure data analysis takes place in an environment where trusted enclaves perform analytics on both data being proffered for the data exchange marketplace and also the “borrowed” data on which an organisation performs their approved analytics on. Conclave and analytics nodes are deployed on Microsoft Azure due to their support of Intel SGX.