English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The scientific method presents a key challenge to privacy because it requiresmany samples to support a claim. When samples are commercially valuable orprivacy-sensitive enough, their owners have strong reasons to avoid releasingthem for scientific study. Privacy techniques seek to mitigate this tension byenforcing limits on one's ability to use studied samples for secondarypurposes. Recent work has begun combining these techniques into end-to-endsystems for protecting data. In this work, we assemble the first suchcombination which is sufficient for a privacy-layman to use familiar tools toexperiment over private data while the infrastructure automatically prohibitsprivacy leakage. We support this theoretical system with a prototype within theSyft privacy platform using the PyTorch framework.

Towards General-purpose Infrastructure for Protecting Scientific Data Under Study