Ivan Ortega

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Secure computation: Homomorphic encryption or hardware enclaves?

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Originally posted on Medium: Written by Raluca Ada Popa on September 16, 2021 How to collaborate with confidential data without sharing it. Secure computation has become increasingly popular for protecting the privacy and integrity of data during computation. The reason is that it provides two tremendous advantages. The first advantage is that it offers “encryption in use” in addition to the already existing “encryption at rest” and “encryption in transit”. The “encryption in use” paradigm is important for security because “encryption at rest” protects that data only when it is in storage and “encryption in transit” protects the data only when it is being communicated over the network, but in both cases the data is exposed during computation, namely, while it…

EPIC Lab receives $2M NSF grant to build tools for criminal justice big datasets

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Originally posted on EECS NEWS: Submitted by Magdalene L. Crowley on September 7, 2021 – 1:55pm EPIC Lab receives $2M NSF grant to build tools for criminal justice big datasets CS Prof. Joseph Hellerstein, and Assistant Profs. Aditya Parmeswaran and Sarah Chasins, are among the principal investigators of a new lab that has just received a $2M grant from the National Science Foundation to make big datasets used by the criminal justice system more accessible to non-technical researchers. The Effective Programming, Interaction, and Computation with Data (EPIC) Lab will create tools that utilize machine learning, program synthesis, and human-centered design, to improve the ability of public defenders, investigators and paralegals to research police misconduct, judicial decision-making, and related issues, for their…