FIVER – Robust Verification of Countermeasures against Fault Injections
DOI:
https://doi.org/10.46586/tches.v2021.i4.447-473Keywords:
FIA, Fault Verification, Formal Verification, BDD, Symbolic SimulationAbstract
Fault Injection Analysis is seen as a powerful attack against implementations of cryptographic algorithms. Over the last two decades, researchers proposed a plethora of countermeasures to secure such implementations. However, the design process and implementation are still error-prone, complex, and manual tasks which require long-standing experience in hardware design and physical security. Moreover, the validation of the claimed security is often only done by empirical testing in a very late stage of the design process. To prevent such empirical testing strategies, approaches based on formal verification are applied instead providing the designer early feedback.
In this work, we present a fault verification framework to validate the security of countermeasures against fault-injection attacks designed for ICs. The verification framework works on netlist-level, parses the given digital circuit into a model based on Binary Decision Diagrams, and performs symbolic fault injections. This verification approach constitutes a novel strategy to evaluate protected hardware designs against fault injections offering new opportunities as performing full analyses under a given fault models.
Eventually, we apply the proposed verification framework to real-world implementations of well-established countermeasures against fault-injection attacks. Here, we consider protected designs of the lightweight ciphers CRAFT and LED-64 as well as AES. Due to several optimization strategies, our tool is able to perform more than 90 million fault injections in a single-round CRAFT design and evaluate the security in under 50 min while the symbolic simulation approach considers all 2128 primary inputs.
Published
Issue
Section
License
Copyright (c) 2021 Jan Richter-Brockmann, Aein Rezaei Shahmirzadi, Pascal Sasdrich, Amir Moradi, Tim Güneysu
This work is licensed under a Creative Commons Attribution 4.0 International License.