What is differential privacy and how can it protect consumer data?
As users become increasingly protective over their data, Deakin University’s Tianqing Zhu explores a simple mathematical solution to the problem of privacy in this crossposting from The Conversation.
It’s no secret that big tech companies like Facebook, Google, Apple and Amazon are increasingly infiltrating our personal and social interactions to collect vast amounts of data on us every day. At the same time, privacy violations in cyberspace regularly make front page news.
So how should privacy be protected in a world where data is gathered and shared with increasing speed and ingenuity?
Differential privacy is a new model of cyber security that proponents claim can protect personal data far better than traditional methods.
The maths it is based on was developed 10 years ago, and the method has been adopted by Apple and Google in recent years.
… as it has always been with reputable research businesses.
Nothing to see here – move along.