From Precise to Random: A Systematic Differential Fault Analysis of the Lightweight Block Cipher Lilliput

2026-03-20

AI Summary

This work systematically evaluates the practical resilience of the lightweight block cipher Lilliput against differential fault analysis (DFA), addressing a critical gap in its physical fault tolerance assessment. We introduce, for the first time, a three-tier progressive nibble-level fault model that relaxes assumptions from multi-round fixed-location injections to single-round fully random fault positions. By integrating DFA with constraints derived from the cipher’s difference distribution table, diffusion properties, and fault localization techniques, we achieve highly efficient key recovery. Experimental results demonstrate that only 8, 8, and 36 fault injections are required under the three respective models to recover the full secret key with success rates exceeding 98%–99.5%, revealing significant vulnerability to realistic fault attacks in practical deployments.

Technology Category

• Natural Language Processing: Safety and Robustness
• Machine Learning: Adversarial Learning & Robustness
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

At SAC 2013, Berger et al. first proposed the Extended Generalized Feistel Networks (EGFN) structure for the design of block ciphers with efficient diffusion. Later, based on the Type-2 EGFN, they instantiated a new lightweight block cipher named Lilliput (published in IEEE Transactions on Computers, Vol. 65, Issue 7, 2016). According to published cryptanalysis results, Lilliput is sufficiently secure against theoretical attacks such as differential, linear, boomerang, and integral attacks, which rely on the statistical properties of plaintext and ciphertext. However, there is a lack of analysis regarding its resistance to physical attacks in real-world scenarios, such as fault attacks. In this paper, we present the first systematic differential fault analysis (DFA) of Lilliput under three nibble-oriented fault models with progressively relaxed adversarial assumptions to comprehensively assess its fault resilience. In Model I (multi-round fixed-location), precise fault injections at specific rounds recover the master key with a 98% success rate using only 8 faults. Model II (single-round fixed-location) relaxes the multi-round requirement, demonstrating that 8 faults confined to a single round are still sufficient to achieve a 99% success rate by exploiting Lilliput's diffusion properties and DDT-based constraints. Model III (single-round random-location) further weakens the assumption by allowing faults to occur randomly among the eight rightmost branches of round 27. By uniquely identifying the fault location from ciphertext differences with high probability, the attack remains highly feasible, achieving over 99% success with 33 faults and exceeding 99.5% with 36 faults. Our findings reveal a significant vulnerability of Lilliput to practical fault attacks across different adversary capabilities in real-world scenarios, providing crucial insights for its secure implementation.

Problem

• differential fault analysis
• lightweight block cipher
• fault attack
• Lilliput
• physical security

Innovation

• Differential Fault Analysis
• Lilliput
• Lightweight Block Cipher
• Fault Injection
• EGFN