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Journal Articles IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems Year : 2023

Delfines: Detecting Laser Fault Injection Attacks Via Digital Sensors

Abstract

Laser Fault Injection Attacks (LFIA) are a major concern in physical security of electronic circuits as they allow an attacker to inject a fault with a very high spatial accuracy. They are also often considered by Information Technology Security Evaluation Facilities (ITSEFs) to deliver security certification, as Common Criteria, of embedded systems. Time or spatial redundancy can be foreseen as protection methods but they are costly and do not ensure immunity against multiple laser injections. The detection would be efficient if the detecting sensors meet enough density and sensitivity to cover the functional blocks being protected. Most sensors rely on analog and specific technology. In this paper, we propose a method to detect LFIAs via a fully digital sensor based on a Time to Digital Converter (TDC) and show its efficacy in detecting such faults in various conditions related to the current induced by the laser, the characteristics of the Power Grid Network (PGN) of the circuit and the environmental variables (voltage, temperature). The simulation results obtained using a 45nm Nangate technology confirms the high efficiency of the proposed scheme in detecting LFIAs in a large range of such conditions.
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Dates and versions

hal-04260842 , version 1 (26-10-2023)

Identifiers

Cite

Mohammad Ebrahimabadi, Suhee Sanjana Mehjabin, Raphael Viera, Sylvain Guilley, Jean-Luc Danger, et al.. Delfines: Detecting Laser Fault Injection Attacks Via Digital Sensors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023, pp.1-1. ⟨10.1109/TCAD.2023.3322623⟩. ⟨hal-04260842⟩
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