The Fog, a New Encrypted Cloud Platform, Rolls In

· Source: IEEE Spectrum · Field: Technology & Digital — Cloud Computing & IT Infrastructure, Cybersecurity & Data Privacy, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Niobium, a chip startup, launched "the Fog," an encrypted cloud platform designed to keep data opaque during computation, addressing the risk of data exposure inherent in traditional cloud services that decrypt data for processing. The Fog utilizes fully homomorphic encryption (FHE), a cryptographic technique that allows computations on encrypted data without decryption. To mitigate FHE's typical performance and memory bottlenecks, Niobium employs its Mistic FPGA chip, which reportedly runs FHE twice as fast as current GPUs for some applications. The platform offers template applications, such as encrypted semantic search, to demonstrate its utility for sensitive data like legal documents. Niobium plans a public launch in May or June and is developing an application-specific integrated circuit (ASIC) projected to be up to 25 times faster than a GPU for its platform.

Key takeaway

For CTOs evaluating cloud security and data privacy solutions, Niobium's Fog platform offers a fundamentally new trust model by ensuring data remains encrypted even during processing. This significantly reduces risks from data leakage and insider threats, enabling safe processing of highly sensitive information in the cloud. You should explore its private beta or public launch to assess its fit for your organization's compliance and security needs, especially for applications involving financial or medical records.

Key insights

The Fog platform enables secure cloud computation on perpetually encrypted data using fully homomorphic encryption and specialized hardware.

Principles

Method

Niobium's Fog platform encrypts data locally with client-held keys, deploys encrypted workloads to the cloud, and processes them using FHE accelerated by Mistic FPGAs, returning encrypted results only decryptable by the client.

In practice

Topics

Best for: CTO, Investor, VP of Engineering/Data, AI Security Engineer, AI Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by IEEE Spectrum.