In lightweight cryptographic primitives, round functions with only simple operations XOR, modular addition and rotation are widely used nowadays. This kind of ciphers is called ARX ciphers. For ARX ciphers, impossible...In lightweight cryptographic primitives, round functions with only simple operations XOR, modular addition and rotation are widely used nowadays. This kind of ciphers is called ARX ciphers. For ARX ciphers, impossible differential cryptanalysis and zero-correlation linear cryptanalysis are among the most powerful attacks, and the key problems for these two attacks are discovering more and longer impossible differentials(IDs) and zero-correlation linear hulls(ZCLHs). However, finding new IDs and ZCLHs for ARX ciphers has been a manual work for a long time, which has been an obstacle in improving these two attacks. This paper proposes an automatic search method to improve the efficiency of finding new IDs and ZCLHs for ARX ciphers. In order to prove the efficiency of this new tool, we take HIGHT, LEA, SPECK three typical ARX algorithms as examples to explore their longer and new impossible differentials and zero-correlation linear hulls. To the best of our knowledge, this is the first application of automatic search method for ARX ciphers on finding new IDs and ZCLHs. For HIGHT, we find more 17 round IDs and multiple 17 round ZCLHs. This is the first discovery of 17 round ZCLHs for HIGHT. For LEA, we find extra four 10 round IDs and several 9 round ZCLHs. In the specification of LEA, the designers just identified three 10 round IDs and one 7round ZCLH. For SPECK, we find thousands of 6 round IDs and forty-four 6 round ZCLHs. Neither IDs nor ZCLHs of SPECK has been proposed before. The successful application of our new tool shows great potential in improving the impossible differential cryptanalysis and zero-correlation linear cryptanalysis on ARX ciphers..展开更多
Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in ...Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.展开更多
By studying modular invariance properties of some characteristic forms,we prove some new anomaly cancellation formulas which generalize the Han-Zhang and Han-Liu-Zhang anomaly cancellation formulas.
基金supported by the National Natural Science Foundation of China under Grant No. 61572516, 61402523, 61202491, 61272041 and 61272488
文摘In lightweight cryptographic primitives, round functions with only simple operations XOR, modular addition and rotation are widely used nowadays. This kind of ciphers is called ARX ciphers. For ARX ciphers, impossible differential cryptanalysis and zero-correlation linear cryptanalysis are among the most powerful attacks, and the key problems for these two attacks are discovering more and longer impossible differentials(IDs) and zero-correlation linear hulls(ZCLHs). However, finding new IDs and ZCLHs for ARX ciphers has been a manual work for a long time, which has been an obstacle in improving these two attacks. This paper proposes an automatic search method to improve the efficiency of finding new IDs and ZCLHs for ARX ciphers. In order to prove the efficiency of this new tool, we take HIGHT, LEA, SPECK three typical ARX algorithms as examples to explore their longer and new impossible differentials and zero-correlation linear hulls. To the best of our knowledge, this is the first application of automatic search method for ARX ciphers on finding new IDs and ZCLHs. For HIGHT, we find more 17 round IDs and multiple 17 round ZCLHs. This is the first discovery of 17 round ZCLHs for HIGHT. For LEA, we find extra four 10 round IDs and several 9 round ZCLHs. In the specification of LEA, the designers just identified three 10 round IDs and one 7round ZCLH. For SPECK, we find thousands of 6 round IDs and forty-four 6 round ZCLHs. Neither IDs nor ZCLHs of SPECK has been proposed before. The successful application of our new tool shows great potential in improving the impossible differential cryptanalysis and zero-correlation linear cryptanalysis on ARX ciphers..
基金Project(51275362)supported by the National Natural Science Foundation of ChinaProject(2013M542055)supported by China Postdoctoral Science Foundation Funded
文摘Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.
基金supported by Fok Ying Tong Education Foundation (Grant No.121003)
文摘By studying modular invariance properties of some characteristic forms,we prove some new anomaly cancellation formulas which generalize the Han-Zhang and Han-Liu-Zhang anomaly cancellation formulas.
