Towards AI-driven Optimization of Robust Probing Model-compliant Masked Hardware Gadgets Using Evolutionary Algorithms

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Masked hardware design is a central countermeasure against side-channel analysis (SCA), but its practical deployment remains costly due to the overhead and design complexity of secure implementations. To manage this complexity, modern masked circuits are increasingly built from composable masked building blocks, referred to as gadgets. However, improving the implementation quality of such gadgets is challenging because optimization must not violate formal security requirements. This paper stu