The Sherlock Holmes of AI

Imagine being a passenger in a self-driving car as the vehicle starts veering off the road. It’s not a faulty sensor causing the dangerous situation — it’s a cyberattack. Hackers can access the deep learning (DL) neural networks at the heart of the vehicle’s computer system, compromising the safety of its passengers, as well as other drivers and pedestrians.

Stopping such cyberattacks requires understanding them first, but this can be challenging. Finding a computing system’s exact deep neural network has many roadblocks. They are often proprietary and, therefore, inaccessible to investigators without considerable legal intervention. Another common problem is that they are updated frequently, making it difficult for investigating researchers to access the most current network iteration. But a new tool from Georgia Tech could unlock the mysterious malware on myriad neural networks in everything from self-driving cars to the IMDB entertainment database. AI Psychiatry (AiP) is a postmortem cybersecurity forensic tool that uses artificial intelligence to recover the exact models a compromised machine runs on and discover where the fatal error occurred.