Title
A statistical model for DPA when algorithmic noise is dependent on target.
Abstract
In side-channel attacks, information about any intermediate data except the target data will be considered as noise, namely, the algorithmic noise. Algorithmic noise is always assumed to be independent of the target data. As a result, it is thought to be an equivalence of physical noise. Numerous investigations are built on this intuitive assumption. In this paper, we claim that this assumption is not always true and find the algorithm (e.g., SIMON) for which the algorithmic noise is dependent on the target data. On this condition, we reconsider the issue of success rate estimation and build a modified statistical model to accurately estimate the success rate when the algorithmic noise is dependent on the target data. Finally, experimental results for SIMON algorithm validate the soundness of our methodology. It is also worth mentioning that SIMON is a candidate proposed by the National Security Agency as the standard light-weight block cipher. (C) 2016 John Wiley & Sons, Ltd.
Year
DOI
Venue
2016
10.1002/sec.1662
SECURITY AND COMMUNICATION NETWORKS
Keywords
Field
DocType
statistical model,algorithmic noise,differential power analysis,SIMON,side-channel attack
Power analysis,Block cipher,Computer security,Computer science,United States National Security Agency,Algorithm,Theoretical computer science,Equivalence (measure theory),Statistical model,Side channel attack,Soundness,Communication noise
Journal
Volume
Issue
ISSN
9.0
18.0
1939-0114
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Shuang Qiu121.39
Rui Zhang215817.73
cao334.27
Wei Yang412.37
YongBin Zhou513627.58
Tian Ding600.34