Proceedings of the 2017 International Conference on Information Technology and Intelligent Manufacturing (ITIM 2017)

Security Evolution on the Non-linear Part of SNOW2.0 against Guess and Determine Attack

Authors
Hao Hu, Jianjun Lu
Corresponding Author
Hao Hu
Available Online August 2017.
DOI
10.2991/itim-17.2017.30How to use a DOI?
Keywords
SNOW2.0, Guess and Determine Attack, SNOW1.0, Finite State Machine
Abstract

SNOW 2.0 was proposed by Ekdahl and Johansson as a strengthened version of SNOW 1.0, which was submitted to the NESSIE project, with a variable-length key of 256 bits. The designers of SNOW2.0 improved the resistance against Guess and Determine (GD) attack by introducing two inputs to the Finite State Machine (FSM). In this paper, the results show that the introduction of those two inputs is not optimal. The suggestion on improving the resistance against GD attack for SNOW2.0 is given.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2017 International Conference on Information Technology and Intelligent Manufacturing (ITIM 2017)
Series
Advances in Intelligent Systems Research
Publication Date
August 2017
ISBN
10.2991/itim-17.2017.30
ISSN
1951-6851
DOI
10.2991/itim-17.2017.30How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Hao Hu
AU  - Jianjun Lu
PY  - 2017/08
DA  - 2017/08
TI  - Security Evolution on the Non-linear Part of SNOW2.0 against Guess and Determine Attack
BT  - Proceedings of the 2017 International Conference on Information Technology and Intelligent Manufacturing (ITIM 2017)
PB  - Atlantis Press
SP  - 120
EP  - 123
SN  - 1951-6851
UR  - https://doi.org/10.2991/itim-17.2017.30
DO  - 10.2991/itim-17.2017.30
ID  - Hu2017/08
ER  -