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During 2022 the COED activities will continue to focus on inspiring companies to pick up on Computing on Encrypted Data, utilizing their data to be shared and processed with and by others, but in a confidential manner. A series of webinars will be joined by workshops and white papers on business cases and activities that lead into the development of components and elements that can be used by organisations to be smoothly integrated into their environments. 

Visit the webinar page and register for one or multiple of the up and coming webinars. 

There are different mechanisms to perform this, already existing for many years, but with difficult challenges to apply and considering the specific use cases to decide whether or not they could be utilized. Some of these include FHE (Full Homomorphic Encryption) and MPC (Multi Party Computation).

Homomorphic encryption is a form of encryption allowing one to perform calculations on encrypted data without decrypting it first. The result of the computation is in an encrypted form, when decrypted the output is the same as if the operations had been performed on the unencrypted data.

Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted. In highly regulated industries, such as health care, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing. For example, predictive analytics in health care can be hard to apply due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these privacy concerns are diminished.

Secure multi-party computation (also known as secure computation, multi-party computation (MPC), or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other.

The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Note that traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while computing with the data from many sources, and correctly producing outputs.

LSEC will develop activities to disseminate the works, and reach out to end users, technology companies and developers and integrators to explore the development of specific use cases and testing of technologies, or validating business models. 

Please reach out to coed at for more information, or join us on the project website : to learn about specific events, activities and other resources than the ones to be found there. 



Explanation by Prof. Dr. Nigel Smart (COSIC - KU Leuven) about MPC 

Slides on MPC and FHE, by Prof. Dr. Nigel Smart. 

Computing on Encrypted Data, by David Wu - University of VIrgina.




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