Here’s how IBM is solving the data privacy problem

• IBM is striving to reduce the barrier to entry so that FHE becomes consumable by all
• Companies are potentially interested in FHE because it would allow them to apply AI to data, such as from finance and health, while being able to promise users that the company has no way to actually view or access it
• Despite the remaining hurdles, Google, IBM, Microsoft and others are pushing to make it easier for developers to leverage the technology

Storing business data these days across hybrid multi cloud environments doesn’t make it less vulnerable to evolving security and data privacy risks. Although encryption provides protection, the data typically must first be decrypted to access it for computing and business-critical operations. Decrypting it inevitably opens the door to potential compromise of privacy and confidentiality controls. 

To such a scenario, there is a powerful solution for organizations that need to process information while still protecting privacy and security: homomorphic encryption. Companies such as Microsoft and Intel have been big proponents of homomorphic encryption. Last December, IBM made a splash when it released its first homomorphic encryption services. That package included educational material, support, and prototyping environments for companies that want to experiment.

Is that how IBM is solving the data privacy problem?

According to an IBM blog post, researchers first started tinkering with homomorphic encryption in the 1970s, but it wasn’t until 2009 when the real pivotal moment came. “It was then that Craig Gentry, back then an IBMer, now — research fellow at Algorand Foundation, published his seminal work, A Fully Homomorphic Encryption Scheme.”

Thanks to this work, researchers and companies began to consider fully homomorphic encryption (FHE) for cloud security, from banking and financial services to online shopping and healthcare. In a recent media presentation on the future of cryptography, IBM director of strategy and emerging technology Eric Maass explained why the company is so bullish on fully homomorphic encryption. “FHE is a unique form of encryption, and it’s going to allow us to compute data that’s still in an encrypted state,” Maass said.

IBM reckons in order to continue its journey into wider use, FHE needs to be in the hands of data scientists and regular application developers, not just cryptography experts. “That’s what we are striving for: to reduce the barrier to entry so that FHE becomes consumable by all,” it added. By working together with leading businesses that understand the unique challenges in their industry and with academics developing and using FHE, IBM has enabled the development of a new generation of AI, machine learning, and cloud technologies that allow critical computations to be performed on sensitive data – without compromising on privacy. 

Other FHE milestones by IBM include working with a select group of clients including Banco Bradesco, one of Brazil’s largest banks, harnessing real financial data. “Researchers showed that it was possible to perform encrypted predictions concealing the data and the result throughout the processing, obtaining the level of privacy not currently possible with any other methods. FHE can provide privacy protection for users requesting predictions— redefining the boundaries of what data must be stored and by whom,” IBM said.

Although there’s still a lot of work to do with FHE, IBM foresees it moving out of research to a broader audience who, they hope, will soon see the value of this technology and take the next steps in improving cloud security. Despite the remaining hurdles, Google, IBM, Microsoft and others are pushing to make it easier for developers to leverage the technology. According to the FHE Market Analysis and Global Outlook Report (2021 to 2026), the key players in the market besides the aforementioned include Galois, CryptoExperts, Enveil, Duality Technologies, ShieldIO, and Huawei.