Statistical Fault Attacks on ASCON Using Improved Square Euclidean Imbalance

In current environment of frequent information exchange between Internet of Things (IoT) devices, traditional cryptographic algorithms often fail to effectively play a role in resource-limited electronic devices, which highlights the importance of lightweight cryptographic algorithms. NIST has completed the standardization process of lightweight cryptographic algorithms, and ASCON has become the ultimate winner. It is foreseeable that its application demand will continue to grow in the future, so the security analysis for ASCON is of significant value. Among various cryptographic algorithm analysis methods, fault attack is an efficient choice. Currently, there are also some fault attack methods for ASCON, but they share a common issue: their time complexity is too high for practical application. In view of this, this paper proposes a more efficient fault attack method for ASCON, including several key points: Firstly, several new statistical scoring functions are constructed based on Square Euclidean Imbalance (SEI). Secondly, a single S-box fault model is proposed to reduce the complexity of injection. Lastly, the complete key is recovered by combining Statistical Invalid Fault Attack (SIFA), Statistical Effective Fault Attack (SEFA), and Statistical Hybrid Fault Attack (SHFA). The time complexity is 216.57, 214.91, and 214.52, respectively. Experimental results on a Python implementation of ASCON, the results show that our scheme significantly reduces the time complexity of attacks, which can provide warnings for cryptography design and applications, and pay more attention to avoiding such risks.