Not so greedy: Enhanced subset exploration for nonrandomness detectors

Linus Karlsson; Martin Hell; Paul Stankovski

doi:10.1007/978-3-319-93354-2_13

Not so greedy: Enhanced subset exploration for nonrandomness detectors

Linus Karlsson, Martin Hell, Paul Stankovski

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › Research › peer-review

1 Citation (SciVal)

120 Downloads (Pure)

Abstract

Distinguishers and nonrandomness detectors are used to distinguish ciphertext from random data. In this paper, we focus on the construction of such devices using the maximum degree monomial test. This requires the selection of certain subsets of key and IV-bits of the cipher, and since this selection to a great extent affects the final outcome, it is important to make a good selection. We present a new, generic and tunable algorithm to find such subsets. Our algorithm works on any stream cipher, and can easily be tuned to the desired computational complexity. We test our algorithm with both different input parameters and different ciphers, namely Grain-128a, Kreyvium and Grain-128. Compared to a previous greedy approach, our algorithm consistently provides better results.

Original language	English
Title of host publication	Information Systems Security and Privacy - 3rd International Conference, ICISSP 2017, Revised Selected Papers
Publisher	Springer
Pages	273-294
Number of pages	22
ISBN (Print)	9783319933535
DOIs	https://doi.org/10.1007/978-3-319-93354-2_13
Publication status	Published - 2018 Jan 1
Event	International Conference on Information Systems Security and Privacy - Porto, Portugal Duration: 2017 Feb 19 → 2017 Feb 21 Conference number: 3 http://icissp.org

Publication series

Name	Communications in Computer and Information Science
Volume	867
ISSN (Print)	1865-0929

Conference

Conference	International Conference on Information Systems Security and Privacy
Abbreviated title	ICISSP
Country/Territory	Portugal
City	Porto
Period	2017/02/19 → 2017/02/21
Internet address	http://icissp.org

Subject classification (UKÄ)

Signal Processing

Keywords

Distinguisher
Grain-128
Grain-128a
Kreyvium
Maximum degree monomial
Nonrandomness detector

Access to Document

10.1007/978-3-319-93354-2_13

karlsson-notsogreedyAccepted author manuscript, 480 KB

Cite this

@inproceedings{971eb7938fba446e96e1a69cbe6d1cfe,

title = "Not so greedy: Enhanced subset exploration for nonrandomness detectors",

abstract = "Distinguishers and nonrandomness detectors are used to distinguish ciphertext from random data. In this paper, we focus on the construction of such devices using the maximum degree monomial test. This requires the selection of certain subsets of key and IV-bits of the cipher, and since this selection to a great extent affects the final outcome, it is important to make a good selection. We present a new, generic and tunable algorithm to find such subsets. Our algorithm works on any stream cipher, and can easily be tuned to the desired computational complexity. We test our algorithm with both different input parameters and different ciphers, namely Grain-128a, Kreyvium and Grain-128. Compared to a previous greedy approach, our algorithm consistently provides better results.",

keywords = "Distinguisher, Grain-128, Grain-128a, Kreyvium, Maximum degree monomial, Nonrandomness detector",

author = "Linus Karlsson and Martin Hell and Paul Stankovski",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/978-3-319-93354-2_13",

language = "English",

isbn = "9783319933535",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "273--294",

booktitle = "Information Systems Security and Privacy - 3rd International Conference, ICISSP 2017, Revised Selected Papers",

address = "Germany",

note = "International Conference on Information Systems Security and Privacy, ICISSP ; Conference date: 19-02-2017 Through 21-02-2017",

url = "http://icissp.org",

}

Karlsson, L, Hell, M & Stankovski, P 2018, Not so greedy: Enhanced subset exploration for nonrandomness detectors. in Information Systems Security and Privacy - 3rd International Conference, ICISSP 2017, Revised Selected Papers. Communications in Computer and Information Science, vol. 867, Springer, pp. 273-294, International Conference on Information Systems Security and Privacy, Porto, Portugal, 2017/02/19. https://doi.org/10.1007/978-3-319-93354-2_13

Not so greedy : Enhanced subset exploration for nonrandomness detectors. / Karlsson, Linus; Hell, Martin ; Stankovski, Paul.

Information Systems Security and Privacy - 3rd International Conference, ICISSP 2017, Revised Selected Papers. Springer, 2018. p. 273-294 (Communications in Computer and Information Science; Vol. 867).

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › Research › peer-review

TY - GEN

T1 - Not so greedy

T2 - International Conference on Information Systems Security and Privacy

AU - Karlsson, Linus

AU - Hell, Martin

AU - Stankovski, Paul

N1 - Conference code: 3

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Distinguishers and nonrandomness detectors are used to distinguish ciphertext from random data. In this paper, we focus on the construction of such devices using the maximum degree monomial test. This requires the selection of certain subsets of key and IV-bits of the cipher, and since this selection to a great extent affects the final outcome, it is important to make a good selection. We present a new, generic and tunable algorithm to find such subsets. Our algorithm works on any stream cipher, and can easily be tuned to the desired computational complexity. We test our algorithm with both different input parameters and different ciphers, namely Grain-128a, Kreyvium and Grain-128. Compared to a previous greedy approach, our algorithm consistently provides better results.

AB - Distinguishers and nonrandomness detectors are used to distinguish ciphertext from random data. In this paper, we focus on the construction of such devices using the maximum degree monomial test. This requires the selection of certain subsets of key and IV-bits of the cipher, and since this selection to a great extent affects the final outcome, it is important to make a good selection. We present a new, generic and tunable algorithm to find such subsets. Our algorithm works on any stream cipher, and can easily be tuned to the desired computational complexity. We test our algorithm with both different input parameters and different ciphers, namely Grain-128a, Kreyvium and Grain-128. Compared to a previous greedy approach, our algorithm consistently provides better results.

KW - Distinguisher

KW - Grain-128

KW - Grain-128a

KW - Kreyvium

KW - Maximum degree monomial

KW - Nonrandomness detector

UR - http://www.scopus.com/inward/record.url?scp=85049107964&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-93354-2_13

DO - 10.1007/978-3-319-93354-2_13

M3 - Paper in conference proceeding

AN - SCOPUS:85049107964

SN - 9783319933535

T3 - Communications in Computer and Information Science

SP - 273

EP - 294

BT - Information Systems Security and Privacy - 3rd International Conference, ICISSP 2017, Revised Selected Papers

PB - Springer

Y2 - 19 February 2017 through 21 February 2017

ER -

Not so greedy: Enhanced subset exploration for nonrandomness detectors

Abstract

Publication series

Conference

Subject classification (UKÄ)

Keywords

Access to Document

Other files and links

Fingerprint

Contributions to Preventive Measures in Cyber Security

Cite this