Introducing HEIR: Google’s Open-Source Tool for Running AI on Encrypted Data
Google has recently introduced HEIR (Homomorphic Encryption Intermediate Representation), a revolutionary open-source compiler toolchain. This innovative tool allows AI models to run inference directly on encrypted data. This means that servers never need to access or see the underlying private information.
The tool was highlighted this week on Google’s Security Blog as part of the company’s Private Computing Toolkit. HEIR is designed to make fully homomorphic encryption (FHE) accessible to everyday developers, without requiring expert-level cryptography knowledge.
Historically, FHE has been considered too slow and technically demanding for commercial use. However, Google’s HEIR dramatically lowers the barrier to entry.
Google demonstrated HEIR’s capabilities across four real-world applications:
- A deep learning recommender system
- Credit-card fraud detection
- Network intrusion detection
- A hotword detector
In addition, Google is co-developing dedicated hardware acceleration for HEIR. This is being done in partnership with firms including Belfort, Niobium, Cornami, and Optalysys.
The implications for privacy-sensitive sectors like healthcare, finance, and government are enormous. For instance, with HEIR, a hospital could theoretically allow an AI to analyze a patient’s encrypted medical data. This could be done without the AI or the cloud server running it ever seeing the raw information.
As AI adoption accelerates across industries, tools like HEIR could be the key to building systems that are both intelligent and genuinely privacy-preserving.
Source: Google Security Blog — How Google Is Making Private AI Practical with Homomorphic Encryption