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Erschienen in:
Introduction to Fault Analysis in Cryptography Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

2. ExpFault: An Automated Framework for Block Cipher Fault Analysis

verfasst von : Sayandeep Saha, Debdeep Mukhopadhyay, Pallab Dasgupta

Erschienen in: Automated Methods in Cryptographic Fault Analysis

Verlag: Springer International Publishing

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Abstract

Intentional or unintentional faults in computation or control flow of modern computing systems can be catastrophic if they are exploited maliciously. One of the primary targets of malicious faults are the modern cryptographic primitives—especially the block ciphers. Designing precise countermeasures against such threats is desirable, but that requires comprehensive knowledge about the attack space of the cryptographic algorithm as well as the implementation. Although manual efforts for vulnerability analysis of fault attacks is quite widespread, it becomes infeasible with the fact that the number of existing ciphers is quite large today. Formidable size of fault spaces and their diversity further highlights the need for automation in this context. Since fault attacks for block ciphers are critically dependent on the mathematical properties of the cipher, a comprehensive understanding of the attack space thus should begin with automated algorithmic analysis. This chapter lays the foundations for automated fault analysis of ciphers and presents a framework called ExpFault for automated algorithm-level fault analysis.

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Vorheriges Kapitel Introduction to Fault Analysis in Cryptography
Nächstes Kapitel Exploitable Fault Space Characterization: A Complementary Approach
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Fußnoten
1
In fact, recently there is a call from National Institute of Standards and Technology (NIST) for standardizing lightweight cipher designs (available online at https://​csrc.​nist.​gov/​Projects/​Lightweight-Cryptography).
 
2
Fault attack countermeasures, in general, are resource-hungry.
 
3
This claim is certainly not restricted to DFAs only and is valid for other classes of fault attacks as well.
 
4
We refer to [20] for the proof of optimality.
 
5
In the next chapter, we shall present another framework which fully utilizes the aforementioned advantage of AFA while making it fairly scalable.
 
6
z = 1, 2, …, l.
 
7
Values of \(w^{ij}_z\) belongs to the set {0, 1, …2m − 1}.
 
8
\({p {'}}^{~w^{ij}_z}_q := \frac {\#q}{|T_{w^{ij}_z}|}\), where #q denote the frequency of q ∈{0, 1, …2m − 1} in \(T_{w^{ij}_z}\).
 
9
VarCount returns the number of variables in a variable set.
 
10
Calculate the probability distribution of each variable set.
 
11
Calculate the entropy of variable sets.
 
12
This is in contrast to the last subsection, where they (the states) were represented as vectors of variables of size m bits.
 
13
We have described the distinguisher corresponding to this attack in Example 2.2.
 
14
The IDFA distinguisher was described in Example 2.1.
 
15
Note that we have used the term “group” to differentiate it from the variable sets. From this point onwards, we shall use variable set and variable group to identify these two separate entities. Variable sets can be members of variable groups.
 
16
The distinguisher here simultaneously extracts round keys from the last two rounds of PRESENT. Total 128 key bits are extracted which can uniquely determine the 80 bit master key by using key scheduling equations.
 
17
BitCount returns the number of bit variables in (MKS h).
 
18
Following the terminology used in this chapter, here we have |MKS h| = 8 and |V G h| = 4.
 
19
For each choice of 28th and 27th round keys we have 23.53 choices for 26th and 25 round keys combined.
 
20
In fact, all the itemsets found for GIFT were spurious and the cipher does not have variable associations. In such cases, the support can be increased to stop spurious itemset generation.
 
21
One should note that the tool is still in its initial phase and we shall try to address all the above-mentioned issues before making it open source.
 
22
Refer to Table 2.4 for the description of the distinguishers.
 
23
The round constant bits of GIFT cipher are not shown in the graphs as they are found to have no effect on the DFA complexity calculation.
 
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Metadaten
Titel
ExpFault: An Automated Framework for Block Cipher Fault Analysis
verfasst von
Sayandeep Saha
Debdeep Mukhopadhyay
Pallab Dasgupta
Copyright-Jahr
2019
Buch
Automated Methods in Cryptographic Fault Analysis

Print ISBN: 978-3-030-11332-2

Electronic ISBN: 978-3-030-11333-9

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-11333-9_2

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