2022
DOI: 10.1007/978-3-030-95085-9_3
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MILP Based Differential Attack on Round Reduced WARP

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Cited by 10 publications
(4 citation statements)
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“…in ¼ 0x0076 0000 0000 0000 0000 c000 00c6 0000 Γ 7 out ¼ 0x0000 000c 0200 0000 0000 100c 0060 0000 in ¼ 0xa000 005a 00f 0 00aa 0000 0000 5000 005f Γ 19 out ¼ 0x0000 0005 0000 0a0a 0000 0005 00f 0 00a0 2 −66 149,447 2 −120:01 20 Γ 20 in ¼ 0x5000 00aa 0050 00b5 0000 0000 f 000 00a5 Γ 20 out ¼ 0x0000 a50a a050 0000 0005 0a0a fa00 0000 The results show that there are at least 64,242 trails within the linear hull with a fixed correlation 2 −72 . These findings provide insights into the clustering effect and distribution of trails within linear hulls for different rounds of WARP.…”
Section: Roundmentioning
confidence: 99%
“…in ¼ 0x0076 0000 0000 0000 0000 c000 00c6 0000 Γ 7 out ¼ 0x0000 000c 0200 0000 0000 100c 0060 0000 in ¼ 0xa000 005a 00f 0 00aa 0000 0000 5000 005f Γ 19 out ¼ 0x0000 0005 0000 0a0a 0000 0005 00f 0 00a0 2 −66 149,447 2 −120:01 20 Γ 20 in ¼ 0x5000 00aa 0050 00b5 0000 0000 f 000 00a5 Γ 20 out ¼ 0x0000 a50a a050 0000 0005 0a0a fa00 0000 The results show that there are at least 64,242 trails within the linear hull with a fixed correlation 2 −72 . These findings provide insights into the clustering effect and distribution of trails within linear hulls for different rounds of WARP.…”
Section: Roundmentioning
confidence: 99%
“…They also applied the division property to find a 20-round integral distinguisher. WARP has also received third-party analysis which mostly focused on differential cryptanalysis [TB21,KY21]. For example, by employing the FBCT framework, Teh and Biryukov [TB21] investigated the security of WARP against boomerang attacks and introduced a 21-round sandwich distinguisher with probability 2 −121.11 building upon which they mounted a key-recovery attack on 24 rounds.…”
Section: Sandwich Distinguishers For Warpmentioning
confidence: 99%
“…Initially, branch-and-bound based methods were used to construct these relations and various improvements in this approach has been proposed [21]. The major development in this area was application of MILP to construct the optimal differential characteristics [25] [22]. The machine learning based approach has also been used to construct the high probability differential distinguishers [30].…”
Section: Introductionmentioning
confidence: 99%