Demystifying the Commercial Potential of Privacy-Enhancing Technologies

The Mission of the Second Privacy-Enhancing Technology Summit

By 2025 the total amount of data created, captured and consumed is predicted to reach 175 zettabytes. However, much of that data’s value is being wasted due to distrust, as there is fear that the data would be exposed when used, computed on or shared with collaborators, possibly leading to trade secrets being leaked or data protection legislation fines.

This challenge is being overcome as new Privacy-Enhancing Technologies (PETs) are being developed that can extract data value in order to unleash its full commercial, scientific and social potential, without jeopardizing the privacy and security of this information.

The Second Privacy-Enhancing Technology Summit is here to help give clear insight on the commercial potential of PETs, from the points of innovation and investment to the point of adoption for:

  • Organizations processing highly sensitive data on how to overcome data privacy challenges to analyse, compute, process or collaborate on sensitive data so they can achieve their data-driven goals.
  • Investors & Consultants on finding new Privacy-Enhancing Technology solution providers that have a realizable return-on-investment and can solve the business challenges of today and the future.
  • Legal Teams & Regulators in order to understand how different Privacy-Enhancing Technologies can ensure ethical use of data and compliance with associated legislation in Switzerland & the EU.
  • Privacy-Enhancing Technology Providers & Research Institutions in order to uncover what value they can offer to enterprise, investors and technology partners by developing new PETs.

Join us for April 5-6 in Zurich, Switzerland to network with industry professionals who are at the forefront of demystifying the commercial, regulatory, and technical opportunities and challenges surrounding Privacy-Enhancing Technologies.

Privacy-Enhancing Technologies: Confidential Computing (Trusted Execution Environments) | Differential Privacy | Federated Learning & Analytics | Homomorphic Encryption | Secure Multiparty Computation | Synthetic Data | Tokenization | Zero-Knowledge Proofs