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Homomorphic encryption

An encryption method that allows a user to carry out defined operations on a set of encrypted data without ever getting the opportunity to decrypt any parts.

For situations where privacy is paramount, homomorphic encryption provides a mechanism that enables a user to share information to a third party — who can carry out computations on that data — while maintaining confidentiality.

What is it?

A cryptographic mechanism for the secure sharing of data.

What’s in it for you?

Using homomorphic encryption can bolster your reputation as a trustworthy partner.

What are the trade-offs?

This changes the way users and customers interact with your system — dealing with that can incur costs.

How is it being used?

This is ideal for systems where form factors mean passwords are impractical.

What is it?


Homomorphic encryption is a method of allowing certain operations on data while never revealing the actual data itself. 


We are starting to see that these systems are able to deliver adequate performance levels that make them a feasible option for scenarios where privacy is paramount.

What’s in for you?


Trust in your businesses’ data and how it is used — both from a functional and ethical standpoint — has always been important. But going forward, it will be a commercial and moral imperative. 


Your brand strength relies on keeping data safe. Moreover, new trust-first business models can be established that build on the outsourced compute model that homomorphic encryption facilitates.

What are the trade offs?


New styles of encryption, such as homomorphic encryption, will fundamentally change the way in which users and consumers access your systems. 


You may need to change the way your systems before consumers can make use of this technology — either by modifying your existing applications or perhaps the introduction of specialized client-server applications that can deliver the necessary functionality to make this work. This could add costs to your business.

How is it being used?


We are seeing novel use cases all the time. One illustrative example is a medical expert system that calculates the projected risk of disease from your genome. Obviously, the genome and DNA data are very sensitive pieces of information. What if you had a high risk of diabetes and your data leaked? You could find your insurance premiums rising. But suppose the genomic data was encrypted using homomorphic encryption and only allowed certain operations. In that case, the medical service provider could perform the services but never actually see your DNA data.

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