Fault Injection

Fault injection is a technique used to assess the resilience and reliability of complex systems, particularly those employing artificial intelligence, by intentionally introducing errors or faults to observe their impact. Current research focuses on developing efficient fault injection methods for various AI architectures, including deep neural networks (DNNs), spiking neural networks (SNNs), and embedded systems, often employing statistical modeling and machine learning to optimize testing and analysis. This work is crucial for ensuring the safety and dependability of AI-powered systems in critical applications like autonomous vehicles and medical devices, driving advancements in both theoretical understanding and practical implementation of robust AI.