Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/135982
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Type: Journal article
Title: Row, Row, Row Your Boat: How to Not Find Weak Keys in Pilsung
Author: Chuengsatiansup, C.
Ronen, E.
Rose, G.G.
Yarom, Y.
Citation: The Computer Journal, 2023; 66(6):1335-1341
Publisher: Oxford University Press (OUP)
Issue Date: 2023
ISSN: 0010-4620
1460-2067
Statement of
Responsibility: 
Chitchanok Chuengsatiansup, Eyal Ronen, Gregory G. Rose, and Yuval Yarom
Abstract: The Pilsung cipher is part of the North Korean Red Star operating system, which was leaked to the West in 2014. Initial analysis by Kryptos Logic reported a possibility of a class of weak keys due to the use of pseudo-random diffusion. Following this lead, we analyzed the cipher and identified a small class of such weak keys. We developed techniques for searching for a key that belongs to the class. After spending thousands of CPU hours, we found a supposedly weak key for a slightly weaker version of Pilsung, but the key did not behave as we expected. On further investigation we found out a crucial misunderstanding in a critical part of the cipher and that no such class of weak keys exists in Pilsung. Thus, this paper makes two main contributions to the art of cryptanalysis. First, it identifies and shows how to investigate a potential weakness in randomizing diffusion, which although does not exist in Pilsung, may affect future designs. Second, it highlights the need for early verification of results in order to identify errors before expending significant resources.
Keywords: Pilsung; AES; weak keys; differential analysis
Description: Advance Access publication on 19 July 2022
Rights: © The Author(s) 2022. Published by Oxford University Press on behalf of The British Computer Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1093/comjnl/bxac092
Grant ID: http://purl.org/au-research/grants/arc/DE200101577
http://purl.org/au-research/grants/arc/DP210102670
Published version: http://dx.doi.org/10.1093/comjnl/bxac092
Appears in Collections:Computer Science publications

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