Statistical Fault Attacks on ASCON Using Improved Square Euclidean Imbalance

Guosheng Xu, Zihan Wang, Yuque Zhang, Chenyu Wang, Guoai Xu

Abstract: 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 article proposes a more efficient fault attack method for ASCON, including several key points: First, several new statistical scoring function are constructed based on square euclidean imbalance (SEI). Second, a single S-box fault model is proposed to reduce the complexity of injection. Lastly, the complete key is recovered by combining statistical ineffective fault attack (SIFA), statistical effective fault attack (SEFA), and statistical hybrid fault attack (SHFA). The time complexity is $2^{16.57}$ , $2^{14.91}$ , and $2^{14.52}$ , 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.

External IDs:dblp:journals/iotj/XuWZWX25