IBM Fully Homomorphic Encryption

IBM emphasizes potential of homomorphic encryption in delivering stronger data security

Months year after technology giant IBM launched the fully homomorphic encryption (FHE), it now emphasizes how the technology is poised to deliver a much stronger security posture for organizations.

FHE is an emerging technology designed to allow data to remain encrypted even while being processed or analyzed in the cloud or third-party environments. Security researchers all over are trying to find the silver bullet that would keep data safe from any form of attack, but it remains elusive.

The research “Using Fully Homomorphic Encryption to Secure Cloud Computing” by Ihsan Jabbar and Saad Najim, defines homomorphic encryption “as a type of encryption that allows particular computations to be conducted on ciphertext and return an encrypted result, the decrypted result is equal to the result of conducting the operation on the plaintext.”

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Simply put, data will remain encrypted during its journey from sender to designated recipient unbless both parties execute mathematical computations to decrypt. This process hopes to circumvent any unauthorized access.

According to Jabbar and Najim’s research, homomorphic encryption has been around for decades with the concept first suggested by Ronald Rivest and Leonard Adleman. After other researchers introduced various additives over the years, it was Craig Gentry who, in 2009 developed “a fully homomorphic encryption-based system that is able to conduct both of addition and multiplication in the same time.”

Transmission and storage

In a virtual demo, Omri Soceanu, manager, AI Security Group, IBM Research, explained how companies could benefit by enabling FHE to keep corporate data secure.

There are two methods where companies usually encrypt data: transmission and storage.

“If companies want to perform computation over data, then they would have to decrypt it,” Soceanu said. “If any malicious entity get hold of your account on the cloud, they will only see encrypted data but wouldn’t be able to process it. This gives you another layer of security.

IBM made its FHE simple that Soceanu said would not need FHE expertise to learn and apply it.

“There are just a few lines of code and no FHE expertise needed for these lines of code,” Soceanu said. “You don’t have to be familiar with schemes or with parameters or with the different implementation. It is pretty easy to use using Python, which is something that is familiar to all data scientists.


FHE is based on lattice cryptography which is considered “quantum-safe” – or resistant to breakage by future quantum-computing speeds.

“One of the things IBM did during the early part of the research and implementation is to prove that this could work,” said Patrick Bruinsma, client technical manager, IBM Z. “We are working on how can we make this available even if companies don’t have deep level of knowledge of all the research and cryptography and all these deep technical skills that they may assume are required.”

Building on groundwork and tools developed IBM Research and IBM Z, the new IBM Security Homomorphic Encryption Services provide a scalable hosting environment on IBM Cloud, along with consulting and managed services to help clients begin learning about and designing prototype solutions that can take advantage of FHE.

According to IBM, companies can leverage FHE in search, analytics, and artificial intelligence functions “without revealing that data to the underlying service.” This is also aligned with IBM’s security on zero-trust, which greatly limits access to data to very few stakeholders.