FPU2025 - AI-powered design of sustainable secure cryptocircuits

The predoctoral training focuses on the design of sustainable, secure, and reconfigurable cryptographic circuits through the use of artificial intelligence techniques. The objective is to train the PhD candidate in the development of cryptographic hardware that is resilient to physical attacks and adaptive to emerging threats. The main tasks include the design and simulation of cryptographic modules and their countermeasures; the development of machine learning-based tools for the automatic detection of information leakage; the implementation of hardware patching techniques to update countermeasures and assess reconfigurability; the design of PUFs and TRNGs using CMOS and emerging technologies; experimental validation on FPGA and ASIC platforms; and participation in laboratory experiments involving side-channel and fault-injection attacks. The candidate will acquire skills in advanced microelectronics, hardware security, VLSI design methodologies, and the use of EDA tools (Cadence, Synopsys, Mentor), as well as in data analysis and AI techniques applied to secure hardware design. Additionally, the researcher will participate in scientific publications, international research stays, and technology transfer activities with industry partners, completing a comprehensive training program oriented towards academic teaching and research in hardware cryptography.