Deep Learning-Assisted Improved Differential Fault Attacks on Lightweight Stream Ciphers

ArXi:2603.29382v1 Announce Type: cross Lightweight cryptographic primitives are widely deployed in resource-constraint environment, particularly in the Internet of Things (IoT) devices. Due to their public accessibility, these devices are vulnerable to physical attacks, especially fault attacks. Recently, deep learning-based cryptanalytic techniques have nstrated promising results; however, their application to fault attacks remains limited, particularly for stream ciphers.