An interview with Yuxin Wang, a rising star in programming analysis of differential privacy.
This post introduces the concept of attestation with Intel SGX enclaves
In this code tutorial, we implement differential identifiability, a differential privacy definition produced by Jaewoo Lee et al. This definitions helps practitioners to decide in a more intuitive manner what the value of epsilon should be, a major problem in the field.
Interview with Fatemeh Mireshghallah, OpenMined's Featured Contributor for April 2021!
This post is a first introduction to the basic principles of Confidential Computing.
Introduction Install PySyft PyTorch v1.8.1 (1 min) Install other dependencies (6 min) Install syft 0.5.0 (6 min) Testing the environment In
The authors of the paper (Jaewoo Lee et al.) behind this code tutorial proposed bounds for epsilon so that its value may not yield a random output query result that leads to a posterior that is greater than the disclosure risk. In this post, we code their solution.
Observe how a differential privacy infrastructure from the ground up. You'll see use cases that bolster the fact that making the infrastructure “user-centric” is crucial. We also discuss why people are reluctant to use such infrastructure
This is a summary of the talk by Daniel Escudero at the OpenMined Privacy Conference 2020. Daniel Escudero talked about PRIMAL, a framewor
In non-federated settings, adaptive optimization methods have desirable convergence properties. Can federated versions of these adaptive optimizers, including Adagrad, Adam, and Yogi facilitate better convergence in the presence of heterogeneous data?
Interview with Tudor Cebere, OpenMined's Featured Contributor for March 2021!
Summary: We learn best with toy code we can play with and diving into the documentations. This beginner friendly blog post covers a quick an
Summary: Sometimes knowing the basics is important! This beginner friendly blog post covers a quick and easy introduction to Differential Pr
Differential Privacy using PyDP - An introductory tutorial. Here's an outline: What does Differential Privacy try to address? Why doesn't anonymization suffice? PyDP Example Walkthrough
We’re are very excited to announce that OpenMined was yet again selected as a mentor organization for Google Summer of Code (GSoC 2021)! Thi
We’re excited to announce the release of the next course in The Private AI Series, Foundations of Private Computation. In this course, you’l
Introducing Structured Transparency: a systematic approach to analyze privacy issues. Learn how to enable transparency without the risk of misuse.
Privacy is becoming increasingly valuable. As more individuals learn of the risks of data breaches, their own vulnerability to AI monitoring, and their rights to protect their privacy, technology needs must be more compliant than ever.
Interview with Bala Priya, OpenMined's Featured Contributor for February 2021!
What are some of the recent advances in Federated Learning? What challenges do the privacy principles guiding Federated Learning (FL) bring into the system?
What do GPT-2 and GPT-3 know about us?
To improve information flows, we need to understand what exactly is not working today.
Information flows form the basis society. How can we understand them better? Why are they often broken and how can we possibly fix them?
This is a conference talk summary from the OpenMined Privacy Conference 2020 Trends and predictions for privacy startups with:Morgan Mahloc
