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Data science platform that improves privacy Duality Technologies announced today that it raised $ 30 million in a Series B round, bringing the total raised to $ 49 million to date. LG Technology Ventures led the funding with participation from Euclidean Capital, Intel Capital, Hearst Ventures, Team8 and the National Bank of Canada’s corporate venture capital arm NAventures, which Duality says will be used to expand its go-to-market operations and move forward. . your partnerships with technology providers.

Newark, NJ-based Duality was founded in 2016 by Turing Award winner Shafi Goldwasser, MIT Professor Vinod Vaikuntanathan, Kurt Rohloff, Alon Kaufman, and Rina Shainski. Vaikuntanathan is the co-inventor of the fundamental BGV homomorphic encryption scheme, while Rohloff co-created the Palisade Homomorphic Cipher Library, the open source package on which the duality platform is based.

“Duality was launched to enable organizations, both public and private, to collaborate on sensitive data without compromising data privacy and business confidentiality,” Kaufman told VentureBeat via email. “In this era of big data, the need to collaborate on sensitive information continues to grow exponentially, while at the same time, data privacy continues to take center stage, leading to an ever-increasing range of data privacy regulations. global (GDPR, CCPA and others) designed to protect personally identifiable information. Reconciling these two conflicting megatrends requires advanced technological solutions. “

Secure data platform

Duality’s platform, SecurePlus, protects data through a form of encryption called homomorphic encryption (HE). HE allows the calculation of the content of encrypted files using an algorithm known as cryptocurrencies. Cryptocurrencies generate an encrypted result that, when decrypted, exactly matches the result of operations that would have been performed in clear text.

By leveraging advancements in HE, Duality claims it can enable organizations to collaborate on sensitive data without having to expose it.

Companies like Enveil, Inpher, Cosmian, Intel, Microsoft, and IBM are in the process of investigating HE. HE libraries still not fully exploiting modern hardware and they are in at least an order of magnitude slower Than conventional methods, but newer projects like Accelerated Encryption Library cuHE Claim 12-50x speedups on various encrypted tasks over previous approaches. HE transformer – a backend for nGraph, Intel’s neural network compiler – also offers leading performance in some cryptocurrencies.

“Due to the increasing level of regulatory attention paid to data privacy, startups in the field are increasingly attracting venture capital investment, while cloud computing giants… are also investing in investigation. However, it remains an extremely complex field, requiring extensive experience in advanced cryptographic techniques and data science and machine learning, ”said Kaufman. “Duality is unique and sets itself apart from its competitors as it implements a wide range of data science capabilities optimized for HE, providing a wealth of use cases for secure data collaboration.”

Duality says it is engaged with various organizations in the financial services field, including Scotiabank, the Cyber ​​Defense Alliance (a consortium of British and European banks and regulators) and others. The platform was originally tested by Scotiabank and, in collaboration with CDA, implemented a proof-of-concept interbank information exchange system. Duality also partnered with Tel Aviv Sourasky Medical Center to create privacy-preserving higher education solutions for cancer research. And the US Defense Advanced Research Projects Agency (DARPA) recently hired Duality to develop privacy-preserving machine learning and training tools for COVID-19 investigation and response, as well as detection. cybercrime.

Other partners include Oracle’s Financial Crimes and Compliance Management and the aforementioned Intel. In collaboration with Intel, Duality aims to optimize HE-based privacy-enhanced data science and artificial intelligence applications for Intel hardware platforms.

“HE introduces a paradigm shift in the way machine learning is used by making it possible to run machine learning models on encrypted data without ever exposing personally identifiable information or other sensitive characteristics. For example, in financial crime investigations, banks can use artificial intelligence-driven data analysis or machine learning to draw powerful conclusions about suspicious activity, increasing the efficiency of such investigations, ”said Kaufman. “Additionally, recent Duality advancements in hardware acceleration have expanded the range of dataset sizes for which HE is feasible, making artificial intelligence analysis on encrypted datasets even more effective and practical. . In 2009, multiplying two bits homomorphically took half an hour. Today, that same task can be accomplished in just nanoseconds, and experts expect that number to drop to a fraction of a nanosecond in the next few years. “

Duality currently has 35 employees and expects to expand its workforce in the coming months.

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