Read more how secure, compliant, and privacy-protected information sharing can provide organizations with a complete view of customer activity.

Award-winning data scientist Prof. Michael Jordan summarizes what homomorphic encryption can do for the world of privacy-preserving machine learning.

Our evaluation sandbox provides you with a pre-built environment with privacy-protected computations and collaboration workflows. Compute on encrypted data, apply a variety of AI models and practice collaborative analytics projects. Compare your results to computations in the clear and evaluate the accuracy and feasibility of encrypted computations.

In this one-pager, you’ll learn how Duality SecurePlus enables financial institutions to collaborate with their business ecosystem while also ensuring compliance.

For this fireside chat, we invited privacy and compliance experts across law firms, leading banks and the FFIS think tank to discuss the business potential and regulatory challenges associated with cross-border data transfers, and present emerging technology solutions that can help institutions mitigate compliance risks.

Answering questions about the exploration of Privacy-Enhancing Technologies (PETs) that can support financial intelligence sharing and help institutions reconcile AML obligations with privacy compliance. Plus: our recommendations on how the financial services industry can move forward and leverage collective analytics to thwart financial crime.

An explanation of three different information sharing implementations across the financial crime lifecycle: Customer Due Diligence, Transaction Monitoring, and Fraud and Cybercrime Investigations.

Muhammad Ismail and Ted Brownlow, core contributors to the JavaScript (web assembly) port of the PALISADE homomorphic encryption library, discuss the technical capabilities of the WebAssembly/JavaScript port and several examples using NodeJS and a web browser.

This talk by Olu Agunloye (CEO of Aleph0 Capital LLC), a core contributor to the JavaScript (web assembly) port of the PALISADE homomorphic encryption library, introduces the blockchain technology, and describes the use cases where blockchain and homomorphic encryption are used together.

Learn about how Privacy-Enhancing Technologies (PETs) cut the red tape from RWE studies and enable medical institutions to securely collaborate on sensitive data.

Financial intelligence sharing promises institutions the ability to take back the upper hand against financial crime networks. While financial regulators increasingly call upon the industry to share information, data privacy compliance poses barriers to inter-institutional collaboration. In this fireside chat, we present pioneering information sharing projects that leverage PETs and discuss pertinent GDPR obligations that institutions have to take into consideration.

Yuriy Polyakov, PALISADE co-founder and project lead, describes best practices for building efficient homomorphic encryption solutions based on approximate homomorphic encryption. These guidelines are applied to the problem of building efficient privacy-preserving Genome-Wide Association Studies (GWAS).

Alexander Gusev, assistant professor at Harvard Medical School, introduces the application of homomorphic encryption for privacy-preserving genomic analysis, focusing on the application of PALISADE for Genome-Wide Association Studies (GWAS) workloads used in practice.

Yuriy Polyakov, a PALISADE co-founder and project lead, introduces homomorphic encryption over real numbers using the Cheon-Kim-Kim-Song (CKKS) approximate homomorphic encryption scheme. In this talk we discuss its implementation in PALISADE from the perspective of an application developer and illustrate applications written using the CKKS implementation in PALISADE.

Prof. Shafi Goldwasser, Director of the Simons Institute for the Theory of Computing, Professor of Electrical Engineering and Computer Science at the University of California Berkeley, Professor of Electrical Engineering and Computer Science at MIT and Professor of Computer Science and Applied Mathematics at the Weizmann Institute of Science Israel, speaks on how cryptographic models and tools can and should play a role in ensuring the trustworthiness of AI and machine learning and address problems such as privacy of training input, model verification and robustness against adversarial examples.

Don’t miss this great episode of the Encrypted Economy as we expand our journey into the business applications of privacy enhancing technologies, and of course keep an eye on Dr. Kurt Rohloff’s work with Duality and the homomorphic encryption standardization group.

Prof. Shafi Goldwasser's thoughts on the state of data privacy in 2021.

To ensure a truly comprehensive and effective approach to managing risk, it’s time to take the enterprise-wide approach one step further and transform it into industry-wide collaboration, enabling banks to investigate suspicious activity not only within their own walls, but also across them.

Momentum is increasing for information sharing among financial institutions - but first, they must overcome some critical technical challenges.

Yuriy Polyakov, a PALISADE co-founder and project lead, introduces multiparty homomorphic encryption and explains how to use it in PALISADE.