What’s New: Intel, Microsoft Research* and Duality Technologies* are bringing nearly 100 security, privacy and artificial intelligence (AI) community members together to create standards for homomorphic encryption (HE), which is emerging as a leading method to protect privacy in machine learning and cloud computing. The HE standards workshop will take place on Intel’s Santa Clara, California campus on Aug. 17, 2019.
“Many of the AI systems that we use and enjoy today are built on and shaped by data, which can be private and sensitive. As homomorphic encryption gains momentum, Intel is proud to collaborate with Microsoft Research and Duality Technologies on standardizing homomorphic encryption to unlock the power of AI, while still respecting and protecting data privacy.”
–Casimir Wierzynski, senior director, office of the CTO, AI Products Group, Intel
Why It Matters: As more data is collected and used to power AI systems, concerns about privacy are on the rise. A recent study by Intouch International* found that 9 in 10 internet users in the U.S. are concerned about the privacy and security of their personal information online. As interest in privacy preserving methods for machine learning grows, it’s essential for standards to be debated and agreed upon by the community – spanning both business and academia.
“Microsoft has invested heavily in developing Homomorphic Encryption, including the release of Microsoft SEAL for commercial use, as a tool to protect enterprise and consumer privacy, while bringing the full power of ML algorithms to process data in the cloud,” said Kristin Lautner, partner research manager, Cryptography and Privacy Research Group, Microsoft. “The Standardization process for Homomorphic Encryption is a key step towards wider acceptance and adoption of this important new encryption tool by industry and governments world-wide. We are confident that the collaboration between Microsoft, Intel, and Duality Technologies on the 4th Homomorphic Encryption Standardization Workshop will accelerate the standardization process and decrease the time to commercial availability of this important privacy protection tool.”
About the Workshop: Targeted at researchers, application developers, security practitioners and encryption experts, the full-day workshop will provide an introduction to HE, review usability for application developers and real-life applications, present the latest research, and include a group discussion on creating HE standards. For those interested but unable to attend, key takeaways will be available online after the workshop, in addition to an HE webinar series from Microsoft.
How Homomorphic Encryption Works: HE allows AI computation on encrypted data, enabling data scientists and researchers to gain valuable insights without decrypting or exposing the underlying data or models. This is particularly useful in instances where data may be sensitive – such as with medical or financial data.
“As a provider of a data science platform optimized for homomorphic encryption, we are excited to be working with Intel and Microsoft Research on this industry standardization initiative,” said Kurt Rohloff, CTO and co-founder of Duality Technologies and associate professor, New Jersey Institute of Technology. “Homomorphic encryption standards are opening the market to a broad range of participants on all layers of the secure computing stack – industry, science, governments, academia, and beyond. Standards are accelerating the adoption of privacy-enhanced information sharing across regulated industries, helping reconcile data utility and data privacy.”
In 2018, Intel open-sourced HE-Transformer, allowing data scientists to develop neural networks on popular open-source frameworks and then easily deploy them to operate on encrypted data.
More Context: HE-Transfomer for nGraph: Enabling Deep Learning on Encrypted Data | AI & Security Innovations Help Developers Preserve Privacy While Delivering Insight | Rethinking Privacy in the Age of AI | Advancing Both AI and Privacy is Not a Zero-Sum Game | Why it is time to standardize privacy-enhancing technologies | Homomorphic Encryption: Making it Real
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