Google will provide open source access to two of the latest Privacy Enhancement Technologies (PETs) as part of Google’s Protected Computing initiative.
The first tool is an internal Google project called Magritte, which is now live on Github, uses machine learning to detect and blur objects as soon as they appear on the screen. The tool can mask arbitrary objects, for example, license plates, tattoos, etc.
“This code is particularly useful for journalists who want to ensure increased privacy guarantees. Using this open source code, operators can save time blurring objects in video, while knowing that the underlying machine learning algorithm can detect them with high accuracy,” Google wrote in the blog.
One more program – Fully Homomorphic Encryption Transpiler — will allow developers to perform calculations with encrypted data without accessing it. Primarily, the tool, according to Google, will help industries that provide financial and health services, as well as government organizations.
PET has been getting a lot of attention lately, with the White House recently touting the technology, saying it would “allow researchers, doctors and others to glean information from sensitive data without having to access it.” Google noted that this year the US and UK governments are holding a competition to develop PET solutions for financial crimes and health emergencies.
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Google previously added the password-less secure login standard to Chrome 108 stable. Access keys now work in Chrome on desktop and mobile devices running Windows 11, macOS, and Android. Google also lets you sync Android passkeys on other devices through the company’s own password manager or a third-party one that supports it: 1Password and Dashlane are known to support it.
Source: Engadget
