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COED - Computing on Encrypted Data

Applying Full Homomorphic Encryption and MultiPartyComputation

Computing On Encrypted Data is a COOCK project that was awarded by VLAIO in November 2020 to LSEC and KU Leuven COSIC

The project aims to create awareness, support understanding and interest, encourage the use and the application of developments of technologies that allow for changes on encrypted data, without them being decrypted. 


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(Full) Homomorphic Encryption 

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.