REDMOND, Washington, Feb. 18, 2020 /PRNewswire/ -- Samsung SDS and Duality Technologies convened AI research and industry leaders last week at the Microsoft campus in Redmond for a workshop focused on advancing standards for Homomorphic Encryption (HE). The meeting was aimed at expanding the standards defined in earlier meetings of the HE standardization community, comprised of experts representing industry as well as academia and government.
HE enables computations, including machine learning and AI analysis, on encrypted data, allowing data scientists, researchers and businesses to gain valuable insights without decrypting or exposing the underlying data or models – key for enabling data-driven digital transformation in all industries while complying with data privacy regulations. This is particularly useful where sensitive data is used in collaborations – for instance, in privacy-preserving collaboration between multiple healthcare and research centers, or inter-bank cooperation in financial crime investigations.
As a result of the workshop, additional schemes and protocols were included among HE standards, laying the foundation for a broad, interoperable secure computing ecosystem. Creating and defining clear standards is critical to fostering market adoption as Homomorphic Encryption becomes an increasingly practical solution to real-world problems.
"Homomorphic Encryption is over the threshold of market-adoption. Given that multiple HE solutions are being offered – some based on open source libraries and others on proprietary protocols – clear and robust industry standards are critical for customer confidence and adoption of solutions using this advanced privacy-enhancing technology," said Dr. Kurt Rohloff, Co-founder and CTO of Duality. "We are excited to be collaborating with Microsoft, Samsung SDS and other leading practitioners from industry, academia and government to establish a comprehensive, interoperable standards framework that will broaden the utility and adoption of HE as the market-leading privacy-enhancing technology."
Dr. Cho Jihoon, Security Research Center Leader at Samsung SDS said: "We believe this standardization meeting will play a pivotal role in making commercially applicable Homomorphic Encryption technologies, amid the rise of demand in the business sector, to cope with the latest artificial intelligence technologies and enhanced privacy regulations."
International standardization bodies such as the International Telecommunication Union (ITU-T) and representatives of the US government were among those attending the working sessions. The decisions taken will help facilitate the path towards further integration of HE into international security standards. Upcoming standardization meetings will be hosted by the UN/ITU-T and the Swiss Federal Institute of Technology (EPFL) in Geneva and by Samsung SDS in South Korea.
About Duality Technologies
Founded by world-renowned data scientists and cryptographers, Duality Technologies is at the forefront of Privacy Enhancing Technologies (PETs), setting a new standard for privacy-preserving data collaborations. The Duality SecurePlus™ platform, a leader in PET, uniquely combines advanced Homomorphic Encryption and data science, enabling organizations to derive insights without exposing their raw data. Duality was recently recognized as a Gartner "Cool Vendor" for Privacy Preservation in Analytics and was named runner-up in the prestigious RSAC Sandbox competition. For more information, please visit www.duality.cloud.
About Samsung SDS
Samsung SDS was founded in 1985 as software arm of Samsung Group, and has been leading digital innovation and transformation for major clients for over 30 years. With the vision to become a data-driven digital transformation leader, Samsung SDS utilizes advanced technologies such as analytics platforms, AI, blockchain and cloud to serve a diverse range of industries including intelligent manufacturing, global logistics, enterprise mobility, financial services and retail. For more information, visit https://www.samsungsds.com.
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