Preventing AI From Divulging Its Own Secrets

One of the sneakiest ways to spill the secrets of a computer system involves studying its pattern of power usage while it performs operations. That's why researchers have begun developing ways to shield the power signatures of AI systems from prying eyes. Among the AI systems most vulnerable to such attacks are machine learning algorithms that help smart home devices or smart cars automatically recognize different types of images or sounds such as words or music. Such algorithms consist of neural networks designed to run on specialized computer chips embedded directly within smart devices, instead of inside a cloud computing server located in a data center miles away. This physical proximity enables such neural networks to quickly perform computations with minimal delay, but also makes it easy for hackers to reverse-engineer the chip's inner workings using a method known as differential power analysis.