As businesses migrate more workloads to the cloud, data and security have become almost inextricably linked. However, unlocking new uses for that data, especially in order to drive richer Artificial Intelligence (AI) and Machine Learning (ML), will necessitate next-generation protection.
Towards achieving a strong data security, businesses have developed confidential computing, which enables data to remain encrypted when being processed. In addition, after a long period, a security process known as fully homomorphic encryption is on its way out of the laboratories and into the hands of early adopters.
Homomorphic encryption is common among researchers because it offers a level of protection that follows data as it moves between systems. Confidential computing, on the other hand, is more dependent on specialised hardware that can be efficient but still limits in certain ways.
Intel and Microsoft, for example, have been active advocates of homomorphic encryption. IBM made headlines last December when it launched its first homomorphic encryption services. For businesses that want to explore, the kit included instructional materials, support, and prototyping environments.
IBM Director of Strategy and Emerging Technology Eric Maass explained why the company is so bullish on “Fully Homomorphic Encryption” (FHE) in a recent media presentation on the future of cryptography.