Boffins baffled as AI training leaks secrets to canny thieves

Private information can be easily extracted from neural networks trained on sensitive data, according to new research. A paper released on arXiv last week by a team of researchers from the University of California, Berkeley, National University of Singapore, and Google Brain reveals just how vulnerable deep learning is to information leakage. The researchers labelled the problem "unintended memorization" and explained it happens if miscreants can access to the model's code and apply a variety of search algorithms. That's not an unrealistic scenario considering the code for many models are available online. And it means that text messages, location histories, emails or medical data can be leaked.