Showing results for "Machine Learning" in Security & Encryption

In Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour—from inside secretive government organizations to academic workshops at ski chalets to Google's cafeteria—recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes.

The ability to hack AI and the technology industry's lack of effort to secure it is thought by experts to be the biggest unaddressed technology issue of our time. Hacking Artificial Intelligence sheds light on these hacking risks, explaining them to those who can make a difference. This book is the first-ever layman's guide to the new world of hacking AI and introduces the field to thousands of people who should be aware of these risks. From a security perspective, AI is today where the internet was thirty years ago. It is wide open and can be exploited.