New Constellation Research Report Finds that TripleBlind Makes an “Elegant and Easily Verified” Data Privacy Promise
Report Confirms MITRE Engenuity Evaluation of Solution Capabilities
KANSAS CITY, MO — August 9, 2022 – TripleBlind “makes an elegant and easily verified privacy promise … the architecture is simple and there is … no interference with any of the raw data, unlike in the case of homomorphic encryption or differential privacy,” notes a new report on the company from analyst firm Constellation Research. The new report, titled “TripleBlind: a Lateral Approach to Privacy-Enhanced Data Sharing,” is now available on the TripleBlind and Constellation Research websites. TripleBlind is the creator of the most complete and scalable solution for privacy enhancing computation.
“TripleBlind is a leader in the relatively new and fast-evolving category of privacy-enhanced computation (PEC),” notes Steve Wilson, Vice President and Principal Analyst at Constellation Research and the author of the report. “With TripleBlind APIs and user interface, customers have access to secure multiparty computation (SMPC) and other advanced privacy tools,” he notes. Wilson continues, “This includes TripleBlind’s own computationally superior Blind Learning (a patented solution for distributed, privacy-first, regulatory-compliance machine learning at scale), Advanced Encryption Standard (AES) inference, distributed inference, and distributed regression techniques … all data remains localized within the customers’ own networks.”
He goes on to call alternative PEC technologies such as homomorphic encryption, statistical perturbation or pseudonymization “complex and fragile,” while branding others that copy data to an intermediate clean room for hosted analysts as “ones that challenge data localization policies.”
Constellation Confirms Evaluation Completed by MITRE Engenuity
The Constellation report also confirms the findings of an independent analysis completed by MITRE Engenuity of TripleBlind and other cybertechnologies in February 2022. To evaluate these technologies uniformly, the MITRE Engenuity team delineated synthetic use cases that approximated the major types of studies performed in observational research or pragmatic clinical trials over the past year. MITRE then created a list of features its team believed necessary to evaluate each technology against each use case. The team determined four features that were mandatory and five that were desirable. It also identified two business related-metrics that gauged technology readiness and cost of deployment.
Constellation confirmed MITRE Engenuity’s findings that TripleBlind met all four of the mandatory requirements, three of the four desired requirements and partially met two additional desired requirements. In terms of technological readiness, TripleBlind scored as fully operational and low cost in terms of operations and maintenance.
The Constellation report concluded, “The TripleBlind code has undergone rigorous independent evaluation … proving both the fundamental mathematics and its high technology readiness. And the company has impressive reference implementations with prestigious institutions such as the Mayo Clinic.”
- Omdia report, “On the Radar: TripleBlind enables secure data sharing for third-party processing”
- Gartner report, “Market Guide for AI Trust, Risk, and Security Management”
- Now available in the AWS and Azure Marketplaces
- Follow TripleBlind on LinkedIn and Twitter
Combining Data and Algorithms while Preserving Privacy and Ensuring Compliance
TripleBlind has created the most complete and scalable solution for privacy enhancing computation.
The TripleBlind solution is software-only and delivered via a simple API. It solves for a broad range of use cases, with current focus on healthcare and financial services. The company is backed by Accenture, General Catalyst and The Mayo Clinic.
TripleBlind’s innovations build on well understood principles, such as federated learning and multi-party compute. Our innovations radically improve the practical use of privacy preserving technologies, by adding true scalability and faster processing, with support for all data and algorithm types. We support all cloud platforms and unlock the intellectual property value of data, while preserving privacy and ensuring compliance with all known data privacy and data residency standards, such as HIPAA and GDPR.
TripleBlind compares favorably with existing methods of privacy preserving technology, such as homomorphic encryption, synthetic data and tokenization and has documented use cases for more than two dozen mission critical business problems.
For an overview, a live demo, or a one-hour hands-on workshop, firstname.lastname@example.org.