Yesterday at the WWDC keynote, Apple announced a series of new security and privacy features, including one feature that’s drawn a bit of attention — and confusion. Specifically, Apple …
Differential Privacy | Harvard University Privacy Tools Project
Please see below for further information about differential privacy and our group's work. To get involved, please email privacytools-info@seas.harvard.edu and see our calls for summer interns, students, postdocs and visiting scholars.
Differential Privacy
A robust yet accessible introduction to the idea, history, and key applications of differential privacy—the gold standard of algorithmic privacy protection
Measuring the Privacy Experience
How do you know that a product respects your privacy – other than by wading through the fine print? We’ve created a framework to measure the way people actually experience privacy in tech products.
Apple Intelligence Promises Better AI Privacy. Here’s How It Actually Works
Private Cloud Compute is an entirely new kind of infrastructure that, Apple’s Craig Federighi tells WIRED, allows your personal data to be “hermetically sealed inside of a privacy bubble.”
Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem
At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy principles, and…
Why the iPhone X's facial recognition could be a privacy disaster
Experts say the technology exposes us to privacy and security risks.
Privacy by Design
In view of rapid and dramatic technological change, it is important to take the special requirements of privacy protection into account early on, because new technological systems often contain hidden dangers which are very difficult to overcome after the basic design has been worked out. So it makes all the more sense to identify and examine possible data protection problems when designing new technology and to incorporate privacy protection into the overall design, instead of having to come up with laborious and time-consuming “patches” later on. This approach is known as “Privacy by Design” (PbD).
Differential Privacy
In 1977 Dalenius articulated a desideratum for statistical databases: nothing about an individual should be learnable from the database that cannot be learned without access to the database. We give a general impossibility result showing that a formalization of Dalenius’ goal along the lines of semantic security cannot be achieved. Contrary to intuition, a variant […]
Potential uses for the Privacy Sandbox
Today on The Keyword, we outlined our vision for an initiative aimed at evolving the web with architecture that advances privacy, while co...
Analysis | Apple is sharing your face with apps. That’s a new privacy worry.
Is Apple doing enough to protect your face?
A Cypherpunk's Manifesto
Privacy is necessary for an open society in the electronic age. Privacy is not secrecy. A private matter is something one doesn't want the whole world to know, but a secret matter is something one doesn't want anybody to know. Privacy is the power to selectively reveal oneself to the world.
Privacy is a collective concern
When we tell companies about ourselves, we give away details about others, too.
Private Cloud Compute: A new frontier for AI privacy in the cloud - Apple Security Research
Secure and private AI processing in the cloud poses a formidable new challenge. To support advanced features of Apple Intelligence with larger foundation models, we created Private Cloud Compute (PCC), a groundbreaking cloud intelligence system designed specifically for private AI processing. Built with custom Apple silicon and a hardened operating system, Private Cloud Compute extends the industry-leading security and privacy of Apple devices into the cloud, making sure that personal user data sent to PCC isn’t accessible to anyone other than the user — not even to Apple. We believe Private Cloud Compute is the most advanced security architecture ever deployed for cloud AI compute at scale.
Writing PrivacyInfo.xcprivacy: Modelling Apple's Rules
The four keys, the required-reason codes, the checks that catch half-finished privacy manifests, and why round-tripping an existing xcprivacy file matters.
Privacy Principles
Privacy is an essential part of the web. This document provides definitions for privacy and related concepts that are applicable worldwide as well as a set of privacy principles that should guide the development of the web as a trustworthy platform. People using the web would benefit from a stronger relationship between technology and policy, and this document is written to work with both.
Privacy Principles
Privacy is an essential part of the web. This document provides definitions for privacy and related concepts that are applicable worldwide as well as a set of privacy principles that should guide the development of the web as a trustworthy platform. People using the web would benefit from a stronger relationship between technology and policy, and this document is written to work with both.