Authors:
Dr. Jordan BrandtInpher was recognized in an April 2020 report titled Emerging Technologies: Homomorphic Encryption for Data Sharing With Privacy, written by Gartner Analyst Mark Driver. Our company was acknowledged as an Example Vendor in the report, and the report mentioned TFHE in the list of HE Open-Source Projects. TFHE is the world’s fastest open-source fully homomorphic encryption library — and it was built in part by Inpher’s own Nicolas Gama, Mariya Georgieva, and Sergiu Carpov. We are honored to be recognized by Gartner in this report!
In the report, Gartner projected, “By 2025, at least 20% of companies will have a budget for projects that include fully homomorphic encryption (FHE), up from less than 1% today.” It was further mentioned, “Assume the mindset that HE will impact customer expectations and be certain that you are well-positioned to adopt and embrace this inevitable impact by 2025.” We also believe that solutions in the privacy-preserving machine learning and analytics space will gain widespread adoption in the years to come.
According to the report, “Homomorphic encryption can better enable enterprises to leverage the services of third-party providers (typically but not restricted to cloud) by reducing or (in some cases) eliminating privacy concerns.” Further, “HE supports multiple clients working together via anonymous data processing efforts to obtain a collaborative result without allowing other clients or a shared third party to see their specific datasets.”
The report walks through a homomorphic encryption use case and mentions, “HE techniques enable citizens to share their genome data and retain key privacy concerns without the traditional all-or-nothing trust threshold with third-party providers.” The report also acknowledges that “This is, of course, just one example from a seemingly endless list of potential solutions. There are other prominent examples, including banking, fraud detection, criminal investigation and homeland security.”
At Inpher, we have excelled in homomorphic encryption applications. For example, Inpher —in collaboration with CEA and KU Leuven— won 1st place at the 2019 iDash Competition Genome Privacy & Security Competition, which focused on secure genotype imputation using fully homomorphic encryption. If you want to learn more about how your organization can leverage Secret Computing®, reach out to us at [email protected]!
—
Gartner, Emerging Technologies: Homomorphic Encryption for Data Sharing With Privacy, Mark Driver, 23 April 2020