Mathematical Certainty in Data Security – The Rise of Fully Homomorphic Encryption

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Interest in FHE (fully homomorphic encryption) is growing as companies seek more robust data privacy solutions in an increasingly regulated world.

FHE allows data to be processed without ever being decrypted – a breakthrough that could revolutionize industries where data security is paramount.

To delve deeper into this technology, I’m planning to answer some of the most asked questions about FHE, what it is capable of today and its future potential to redefine secure data processing.

What inspired the development of FHE

Homomorphic encryption developed gradually over the past several decades – first by the accidental discovery of partially homomorphic systems and then more purposefully until its full capability emerged in 2009 and the following decade.

The implications of these developments were staggering – we could send data to the cloud, an AI engine or another third party for processing without ever worrying about a resulting privacy breach.

However, the computational power required to implement FHE remained many orders of magnitude greater than computing ‘in the clear,’ making broad adoption a difficult sell, and relegating FHE to an academic endeavor.

Now, however, interest in and advancement of FHE is driven by new forces.

Companies must navigate a complex legal framework encompassing GDPR in Europe, CCPA in California and diverse regulations in at least 14 other US states.

And yet, the commercial appetite for third-party data continues to grow – companies are counting on the ability to ingest new data in order to solve hard problems ranging from detecting financial fraud to researching medical treatments.

At the same time, privacy-assuring alternatives to FHE face significant headwinds.

Confidential computing methods such as TEEs (trusted execution environments) have been shown time and again to be vulnerable to both side-channel attacks and direct breaches, placing the companies that rely on them at risk.

Other privacy-assuring approaches, such as secure multi-party computation, typically require networks of computers to be and stay online together throughout computations – requiring complex network configurations and vulnerable to failure if any one of the participating machines or network links fails.

FHE, on the other hand, has cryptographically sound proofs of privacy, requires no complex network configurations and relies only on a single compute server’s reliability.

This…