Attacks on Tiny AI

As of this year, there are over a 2.5 billion Edge-enabled IoT devices and close to 1.5 million new AI Edge devices projected to be shipped. These devices include smaller compressed versions of AI models running on them. While in the last years, we have been able to improve the performance of the AI models and reduce their memory footprint on these devices, not much has been spoken about the security threats of the AI models on tiny models.

First step towards protecting these AI models from attacks such as Model Theft, evasion and data poisoning, would be to study the efficacy of attacks on these Tiny Intelligent systems. Some of them at the lower Hardware and software layers could be protected through classical embedded security, they alone would not suffice to protect these Tiny Intelligence. Many of these tiny devices (microcontrollers) do not come with built-in security features because of their price and power requirements. So an understanding of how the core AI algorithm could be attacked and protected become necessary. In this talk we go about discussing what could be the possible threats to these devices and provide directions on how additional AI security measures would save the Tiny intelligence.