Accountable JavaScript Code Delivery
We propose Accountable JS, a browser extension and opt-in protocol for accountable delivery of active content on a web page. We prototype our protocol, formally model its...
We propose Accountable JS, a browser extension and opt-in protocol for accountable delivery of active content on a web page. We prototype our protocol, formally model its...
We first present three real-world case studies from which we can glean practical insights unknown or neglected in research. Next we analyze all adversarial ML papers recently...
In August, Meta launched the 2022 People’s Expectations and Experiences with Digital Privacy request for proposals (RFP). Today, it is my sincere honor to announce the winners...
Robust modules guarantee to do only what they are supposed to do – even in the presence of untrusted, malicious clients, and considering not just the direct behavior of...
In this work, we propose a new scheme for upstream communication where instead of transmitting the model update, each client learns and transmits a light-weight synthetic dataset...
In this work, we train transformers to perform modular arithmetic and mix half-trained models with statistical cryptanalysis techniques to propose SALSA: a machine learning...
In this work, we implement the GBDT model under Differential Privacy (DP). We propose a general framework that captures and extends existing approaches for differentially...
In June, WhatsApp launched its first research award opportunity on privacy-aware program analysis. Today, we’re announcing the winners of that award.
We at Meta care deeply about protecting the privacy of our users’ data and that of advertisers and their customers. We’re researching and developing several privacy-enhancing...
In June, Meta launched the 2022 Meta AR/VR Policy Research request for proposals (RFP) in partnership with the Centre for Civil Society and Governance of the University of Hong Kong.