Improved deep learning aided key recovery framework:applications to large-state block ciphers  

作　　者：Xiaowei LI Jiongjiong REN Shaozhen CHEN 

机构地区：[1]School of Cyber Science and Technology,Information Engineering University,Zhengzhou 450000,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2024年第10期1406-1420,共15页信息与电子工程前沿（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(No.62206312)。

摘　　要：At the Annual International Cryptology Conference in 2019,Gohr introduced a deep learning based cryptanalysis technique applicable to the reduced-round lightweight block ciphers with a short block of SPECK32/64.One significant challenge left unstudied by Gohr's work is the implementation of key recovery attacks on large-state block ciphers based on deep learning.The purpose of this paper is to present an improved deep learning based framework for recovering keys for large-state block ciphers.First,we propose a key bit sensitivity test(KBST)based on deep learning to divide the key space objectively.Second,we propose a new method for constructing neural distinguisher combinations to improve a deep learning based key recovery framework for large-state block ciphers and demonstrate its rationality and effectiveness from the perspective of cryptanalysis.Under the improved key recovery framework,we train an efficient neural distinguisher combination for each large-state member of SIMON and SPECK and finally carry out a practical key recovery attack on the large-state members of SIMON and SPECK.Furthermore,we propose that the 13-round SIMON64 attack is the most effective approach for practical key recovery to date.Noteworthly,this is the first attempt to propose deep learning based practical key recovery attacks on18-round SIMON128,19-round SIMON128,14-round SIMON96,and 14-round SIMON64.Additionally,we enhance the outcomes of the practical key recovery attack on SPECK large-state members,which amplifies the success rate of the key recovery attack in comparison to existing results.

关 键 词：Deep learning Large-state block cipher Key recovery Differential cryptanalysis SIMON SPECK 

分 类 号：TN918[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]