ISCAS OpenIR
recursive diffusion layers for (lightweight) block ciphers and hash functions
Wu Shengbao; Wang Mingsheng; Wu Wenling
2013
Conference Name19th International Conference on Selected Areas in Cryptography, SAC 2012
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages355-371
Conference DateAugust 15, 2012 - August 16, 2012
Conference PlaceWindsor, ON, Canada
Indexed TypeEI
ISSN0302-9743
ISBN9783642359989
Department(1) Institute of Software Chinese Academy of Sciences P.O. Box 8718 Beijing 100190 China; (2) Graduate School of Chinese Academy of Sciences Beijing 100190 China; (3) State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China
English AbstractDiffusion layers with maximum branch numbers are widely used in block ciphers and hash functions. In this paper, we construct recursive diffusion layers using Linear Feedback Shift Registers (LFSRs). Unlike the MDS matrix used in AES, whose elements are limited in a finite field, a diffusion layer in this paper is a square matrix composed of linear transformations over a vector space. Perfect diffusion layers with branch numbers from 5 to 9 are constructed. On the one hand, we revisit the design strategy of PHOTON lightweight hash family and the work of FSE 2012, in which perfect diffusion layers are constructed by one bundle-based LFSR. We get better results and they can be used to replace those of PHOTON to gain smaller hardware implementations. On the other hand, we investigate new strategies to construct perfect diffusion layers using more than one bundle-based LFSRs. Finally, we construct perfect diffusion layers by increasing the number of iterations and using bit-level LFSRs. Since most of our proposals have lightweight examples corresponding to 4-bit and 8-bit Sboxes, we expect that they will be useful in designing (lightweight) block ciphers and (lightweight) hash functions. © 2013 Springer-Verlag Berlin Heidelberg.; Diffusion layers with maximum branch numbers are widely used in block ciphers and hash functions. In this paper, we construct recursive diffusion layers using Linear Feedback Shift Registers (LFSRs). Unlike the MDS matrix used in AES, whose elements are limited in a finite field, a diffusion layer in this paper is a square matrix composed of linear transformations over a vector space. Perfect diffusion layers with branch numbers from 5 to 9 are constructed. On the one hand, we revisit the design strategy of PHOTON lightweight hash family and the work of FSE 2012, in which perfect diffusion layers are constructed by one bundle-based LFSR. We get better results and they can be used to replace those of PHOTON to gain smaller hardware implementations. On the other hand, we investigate new strategies to construct perfect diffusion layers using more than one bundle-based LFSRs. Finally, we construct perfect diffusion layers by increasing the number of iterations and using bit-level LFSRs. Since most of our proposals have lightweight examples corresponding to 4-bit and 8-bit Sboxes, we expect that they will be useful in designing (lightweight) block ciphers and (lightweight) hash functions. © 2013 Springer-Verlag Berlin Heidelberg.
KeywordHardware Hash Functions Linear Transformations Lyapunov Methods Matrix Algebra Photons Security Of Data Shift Registers
SponsorshipDepartment of Electrical and Computer Engineering; Faculty of Engineering; Office of Vice President - Research, University of Windsor
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15899
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wu Shengbao,Wang Mingsheng,Wu Wenling. recursive diffusion layers for (lightweight) block ciphers and hash functions[C],2013:355-371.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wu Shengbao]'s Articles
[Wang Mingsheng]'s Articles
[Wu Wenling]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wu Shengbao]'s Articles
[Wang Mingsheng]'s Articles
[Wu Wenling]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wu Shengbao]'s Articles
[Wang Mingsheng]'s Articles
[Wu Wenling]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.