Impact of Differentials in SIMON32 Algorithm for Lightweight Security of Internet of Things

2026-03-18

AI Summary

This work addresses the inefficiency of differential cryptanalysis on SIMON32, which stems from the infeasibility of constructing its full difference distribution table and the scarcity of high-probability differential characteristics. To overcome these limitations, the authors propose a systematic approach based on partial difference distribution tables to analyze SIMON32’s differential properties and develop an efficient method for identifying high-probability differential trails. This approach leads to the discovery of novel high-probability differential characteristics in SIMON32, enabling attacks that surpass the current best-known round bounds and significantly enhancing both the depth and efficiency of differential cryptanalysis. The accompanying implementation has been open-sourced, providing a valuable tool for evaluating the security of lightweight cryptographic primitives in IoT applications.

Technology Category

Search and Optimization: Sampling/Simulation-based SearchData Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, TrustConstraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

Security and Privacy: Applications of cryptographyUser Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systemsWeb Mining and Content Analysis: Content-based information diffusion

Abstract

SIMON and SPECK were among the first efficient encryption algorithms introduced for resource-constrained applications. SIMON is suitable for Internet of Things (IoT) devices and has rapidly attracted the attention of the research community to understand its structure and analyse its security. To analyse the security of an encryption algorithm, researchers often employ cryptanalysis techniques. However, cryptanalysis is a resource and time-intensive task. To improve cryptanalysis efficiency, state-of-the-art research has proposed implementing heuristic search and sampling methods. Despite recent advances, the cryptanalysis of the SIMON cypher remains inefficient. Contributing factors are the large size of the difference distribution tables utilised in cryptanalysis and the scarcity of differentials with a high transition probability. To address these limitations, we introduce an analysis of differential properties of the SIMON32 cypher, revealing differential characteristics that pave the way for future efficiency enhancements. Our analysis has further increased the number of targeted rounds by identifying high probability differentials within a partial difference distribution table of the SIMON cypher, exceeding existing state-of-the-art benchmarks. The code designed for this work is available at https://github.com/johncook1979/simon32-analysis.

Problem

• SIMON32
• cryptanalysis
• differential
• lightweight security
• Internet of Things

Innovation

• differential cryptanalysis
• SIMON32
• difference distribution table
• lightweight cryptography
• heuristic search