TripleBlind vs Homomorphic Encryption banner image

How TripleBlind’s Data Privacy Solution Compares to Homomorphic Encryption

Homomorphic encryption is a technique that allows for computations to be done on encrypted data without needing a secret decryption key, allowing only the owner or those with the secret key to see the results of the computations. There are multiple applications in which fully homomorphic encryption can be applied, from something as simple as keeping a person’s Internet search history private from third-party marketers to more complicated computations such as those done with healthcare data. Homomorphic encryption is considered one of the more well-rounded encryption solutions in the market and has been adopted by tech giants like IBM and Microsoft.

However, homomorphic encryption’s most significant barrier to widespread use is its significant computation overhead and latency. In fact, according to IBM’s homomorphic encryption trials, it requires more than 42-times compute power and 20-times memory compared to other types of encryptions. 

Homomorphic encryption’s speed is not the only place it falls short compared to TripleBlind’s data privacy technology. Below is a comparison chart of the two solutions:

  • TripleBlind
  • Fast
  • Universal, cloud based
  • Future proof
  • Blind inference supports all non-linear operations, including comparisons
  • Requires all parties online
  • All parties consent to each use
  • Mathematical digital rights management
  • Homomorphic Encryption
  • Slow
  • High CPU needs
  • May be cracked in the future
  • Only supports basic algebraic operations
  • Operates offline
  • Doesn’t require consent of all parties for other uses
  • No digital rights management

There are other areas in which homomorphic encryption doesn’t stack up compared to TripleBlind, including:

TripleBlind compared to homomorphic encryption table

As you can see in the above charts, homomorphic encryption falls short in too many categories to provide an enterprise with a complete solution. Enterprises would likely need one or more other solutions to have all the criteria fulfilled. You can read more about homomorphic encryption here.

Unlocking private data sharing with TripleBlind’s solution allows businesses to collaborate more fully, compliantly and across broader horizons than homomorphic encryption. To learn more about how TripleBlind compares to other competitors and methods of data collaborations, follow us on LinkedIn and Twitter to be notified when we post the next installation in our Competitor Blog Series.

If you’d like to schedule a call or free demo to explore how TripleBlind can work for your business, please reach out to

Read the other blogs in this series:
Business Agreements
Synthetic Data
Tokenization, Masking and Hashing
Federated Learning
Differential Privacy