SearcharxivSearch

arXiv subjects

Peipei Xie

Publications and source records attributed to Peipei Xie.

2 recordsLinked to original sources

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

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.

cs.CR

Cryptanalysis of Gleeok-128

Gleeok is a family of low latency keyed pseudorandom functions (PRFs) consisting of three parallel SPN based permutations whose outputs are XORed to form the final value. Both Gleeok-128 and Gleeok-256 use a 256 bit key, with block sizes of 128 and 256 bits, respectively. Owing to its multi branch structure, evaluating security margins and mounting effective key recovery attacks present nontrivial challenges. This paper provides the first comprehensive third party cryptanalysis of Gleeok-128. We introduce a two stage MILP based framework for constructing branch wise and full cipher differential linear (DL) distinguishers, together with an integral based key recovery framework tailored to multi branch designs. Our DL analysis yields 7, 7, 8, and 4 round distinguishers for Branch 1, Branch 2, Branch 3, and Gleeok-128, respectively, with squared correlations approximately 2 to the power minus 88.12, 2 to the power minus 88.12, 2 to the power minus 38.73, and 2 to the power minus 49.04, outperforming those in the design document except for the full PRF case. By tightening algebraic degree bounds, we further derive 9, 9, and 7 round integral distinguishers for the three branches and a 7 round distinguisher for the full PRF, extending the designers results by 3, 3, and 2 rounds and by 2 rounds, respectively. These integral properties enable 7 round and 8 round key recovery attacks in the non full codebook and full codebook settings. In addition, we identify a flaw in the original linear security evaluation of Branch 3, showing that it can be distinguished over all 12 rounds with data complexity about 2 to the power 48. We also propose optimized linear layer parameters that significantly improve linear resistance without sacrificing diffusion. Our results advance the understanding of Gleeok-128 and provide general methods for analyzing multi branch symmetric designs.

cs.CR