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MARTINÁSEK, Z. MALINA, L. TRÁSY, K.
Original Title
Profiling Power Analysis Attack Based on Multi-Layer Perceptron Network
Type
book chapter
Language
English
Original Abstract
In 2013, an innovative method of power analysis was presented. Realized experiments proved that the proposed method based on Multi-Layer Perceptron (MLP) can provide almost 100 percent success rate. This description based on the first-order success rate is not appropriate enough. Moreover, the above mentioned works contain other lacks: the MLP has not been compared with other well-known attacks, an adversary uses too many points of power trace and a general description of the MLP method was not provided. In this paper, we eliminate these weaknesses by introducing the first fair comparison of power analysis attacks based on the MLP and templates. The comparison is accomplished by using the identical data sets, number of interesting points and guessing entropy as a metric. The first data set created contains the power traces of an unprotected AES implementation in order to classify the secret key stored. The second and third data sets were created independently from public available power traces corresponding to a masked AES implementation (DPA Contest v4). Secret offset is revealed depending on the number of interesting points and power traces in this experiment. Moreover, we create a general description of the MLP attack.
Keywords
Power Analysis, MLP, Machine Learning, Template Attack, Comparison.
Authors
MARTINÁSEK, Z.; MALINA, L.; TRÁSY, K.
RIV year
2015
Released
16. 10. 2015
Publisher
Springer International Publishing
Location
Switzerland 2015
ISBN
978-3-319-15764-1
Book
Computational Problems in Science and Engineering
Edition
1
Edition number
Pages from
Pages to
25
Pages count
URL
https://link.springer.com/chapter/10.1007/978-3-319-15765-8_18
BibTex
@inbook{BUT117847, author="Zdeněk {Martinásek} and Lukáš {Malina} and Krisztina {Trásy}", title="Profiling Power Analysis Attack Based on Multi-Layer Perceptron Network", booktitle="Computational Problems in Science and Engineering", year="2015", publisher="Springer International Publishing", address="Switzerland 2015", series="1", edition="1", pages="1--25", doi="10.1007/978-3-319-15765-8\{_}18", isbn="978-3-319-15764-1", url="https://link.springer.com/chapter/10.1007/978-3-319-15765-8_18" }