Intellectual Property (IP) theft is a cause of major financial and reputational damage, reportedly in the range of hundreds of billions of dollars annually in the U.S. alone. Field Programmable Gate Arrays (FPGAs) are particularly exposed to IP theft, because their configuration file contains the IP in a proprietary format that can be mapped to a gate-level netlist with moderate effort. Despite this threat, the scientific understanding of this issue lacks behind reality, thereby preventing an in-depth assessment of IP theft from FPGAs in academia. We address this discrepancy through a real-world case study on a Lattice iCE40 FPGA found inside iPhone 7. Apple refers to this FPGA as Maggie. By reverse engineering the proprietary signal-processing algorithm implemented on Maggie, we generate novel insights into the actual efforts required to commit FPGA IP theft and the challenges an attacker faces on the way. Informed by our case study, we then introduce generalized netlist reverse engineering techniques that drastically reduce the required manual effort and are applicable across a diverse spectrum of FPGA implementations and architectures. We evaluate these techniques on six benchmarks that are representative of different FPGA applications and have been synthesized for Xilinx and Lattice FPGAs, as well as in an end-to-end white-box case study. Finally, we provide a comprehensive open-source tool suite of netlist reverse engineering techniques to foster future research, enable the community to perform realistic threat assessments, and facilitate the evaluation of novel countermeasures.

The application of masking, widely regarded as the most robust and reliable countermeasure against Side-Channel Analysis~(SCA) attacks, has been the subject of extensive research across a range of cryptographic algorithms, especially AES. However, the implementation cost associated with applying such a countermeasure can be significant and even in some scenarios infeasible due to considerations such as area and latency overheads, as well as the need for fresh randomness to ensure the security properties of the resulting design. Most of these overheads originate from the ability to maintain security in the presence of physical defaults such as glitches and transitions. Among several schemes with a trade-off between such overheads, RAMBAM, presented at CHES~2022, offers an ultra-low latency in terms of the number of clock cycles. It is dedicated to the AES and utilizes redundant representations of the finite field elements to enhance protection against both passive and active physical attacks.