Side-channel analysis against SecOC-compliant AES-CMAC

This study presents a side-channel analysis (SCA) attack for AES-CMAC, which is used in the controller area network (CAN) protocol in-vehicle networks. It difficult to apply conventional SCAs that focus on single round of Sboxes as case AES-CMAC/CTR because AES input values are unknown attacker owing its structure. The proposed method focuses first three rounds continuously and obtains secret key by sequentially estimating intermediate using first-order SCA. Our can be applied all versions Secure Onboard Communication (SecOC) standard securing CAN protocols. We deep-learning-based SCA implement attack, addition correlation power analysis. demonstrate effectiveness through an experiment AES-CMAC software implemented PASTA automotive security evaluation platform, compliant with SecOC defined AUTomotive Open System ARchitecture. results show successfully reveal at most 400,000 150 measurements non-profiling SCA, respectively.