Modern RISC-V designs are increasingly integrating cryptographic accelerators to provide better security features while enhancing performance; however, their vulnerability to power side-channel attacks remains insufficiently investigated. This paper presents a comprehensive evaluation of such vulnerabilities in a RISCV-based AES accelerator connected via the Core-V eXtension Interface (CV-X-IF). The analysis begins at the RTL using simulated power traces, employing KL (Kullback–Leibler) divergence alongside established statistical attacks such as Correlation Power Analysis (CPA) and Differential Power Analysis (DPA). Although the former serves as an early indicator of potential leakage, simulation results highlight its limitations compared to CPA and DPA. To validate these findings, leakage trends are further examined through FPGA-based power measurement. The proposed methodology is designed to be broadly applicable to a range of cryptographic workloads and accelerator architectures. It is demonstrated on an AES accelerator implementing the scalar cryptographic extension (Zk) with pre-expanded keys. Our findings reveal that side-channel vulnerabilities can persist even in tightly integrated instruction pipelines, underscoring the importance of early-stage leakage assessment. Notably, the close alignment between RTL-level simulations and FPGA-based measurements highlights the effectiveness of the approach and its practical value for guiding secure hardware design in RISC-V ecosystems. In particular, AES serves only as a case of study; the proposed RTL and FPGA validation flow is generic and can be applied to any cryptographic accelerator.
Power Side-Channel Vulnerabilities of a RISC-V Cryptography Accelerator Integrated into CVA6 via Core-V eXtension Interface (CV-X-IF) / Farnaghinejad, Behnam; Bellizia, Davide; Dolmeta, Alessandra; Masera, Guido; Porsia, Antonio; Ruospo, Annachiara; Di Carlo, Stefano; Savino, Alessandro; Sanchez, Ernesto. - (2025), pp. 1-10. (Intervento presentato al convegno International Test Conference 2025 tenutosi a San Diego, California (USA) nel September 20-26, 2025) [10.1109/ITC58126.2025.00030].
Power Side-Channel Vulnerabilities of a RISC-V Cryptography Accelerator Integrated into CVA6 via Core-V eXtension Interface (CV-X-IF)
Behnam Farnaghinejad;Alessandra Dolmeta;Guido Masera;Antonio Porsia;Annachiara Ruospo;Stefano Di Carlo;Alessandro Savino;Ernesto Sanchez
2025
Abstract
Modern RISC-V designs are increasingly integrating cryptographic accelerators to provide better security features while enhancing performance; however, their vulnerability to power side-channel attacks remains insufficiently investigated. This paper presents a comprehensive evaluation of such vulnerabilities in a RISCV-based AES accelerator connected via the Core-V eXtension Interface (CV-X-IF). The analysis begins at the RTL using simulated power traces, employing KL (Kullback–Leibler) divergence alongside established statistical attacks such as Correlation Power Analysis (CPA) and Differential Power Analysis (DPA). Although the former serves as an early indicator of potential leakage, simulation results highlight its limitations compared to CPA and DPA. To validate these findings, leakage trends are further examined through FPGA-based power measurement. The proposed methodology is designed to be broadly applicable to a range of cryptographic workloads and accelerator architectures. It is demonstrated on an AES accelerator implementing the scalar cryptographic extension (Zk) with pre-expanded keys. Our findings reveal that side-channel vulnerabilities can persist even in tightly integrated instruction pipelines, underscoring the importance of early-stage leakage assessment. Notably, the close alignment between RTL-level simulations and FPGA-based measurements highlights the effectiveness of the approach and its practical value for guiding secure hardware design in RISC-V ecosystems. In particular, AES serves only as a case of study; the proposed RTL and FPGA validation flow is generic and can be applied to any cryptographic accelerator.| File | Dimensione | Formato | |
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https://hdl.handle.net/11583/3001125
