Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147426
Title: SITM : See-In-The-Middle side-channel assisted middle round differential cryptanalysis on SPN block ciphers
Authors: Bhasin, Shivam
Breier, Jakub
Hou, Xiaolu
Jap, Dirmanto
Poussier, Romain
Sim, Siang Meng
Keywords: Science::Mathematics::Discrete mathematics::Cryptography
Issue Date: 2019
Source: Bhasin, S., Breier, J., Hou, X., Jap, D., Poussier, R. & Sim, S. M. (2019). SITM : See-In-The-Middle side-channel assisted middle round differential cryptanalysis on SPN block ciphers. IACR Transactions On Cryptographic Hardware and Embedded Systems, 2020(1), 95-122. https://dx.doi.org/10.13154/tches.v2020.i1.95-122
Journal: IACR Transactions on Cryptographic Hardware and Embedded Systems 
Abstract: Side-channel analysis constitutes a powerful attack vector against cryptographic implementations. Techniques such as power and electromagnetic side-channel analysis have been extensively studied to provide an efficient way to recover the secret key used in cryptographic algorithms. To protect against such attacks, countermeasure designers have developed protection methods, such as masking and hiding, to make the attacks harder. However, due to significant overheads, these protections are sometimes deployed only at the beginning and the end of encryption, which are the main targets for side-channel attacks. In this paper, we present a methodology for side-channel assisted differential cryptanalysis attack to target middle rounds of block cipher implementations. Such method presents a powerful attack vector against designs that normally only protect the beginning and end rounds of ciphers. We generalize the attack to SPN based ciphers and calculate the effort the attacker needs to recover the secret key. We provide experimental results on 8-bit and 32-bit microcontrollers. We provide case studies on state-of-the-art symmetric block ciphers, such as AES, SKINNY, and PRESENT. Furthermore, we show how to attack shuffling-protected implementations.
URI: https://hdl.handle.net/10356/147426
ISSN: 2569-2925
DOI: 10.13154/tches.v2020.i1.95-122
Schools: School of Computer Science and Engineering 
Research Centres: Temasek Laboratories @ NTU 
Rights: © 2019 Shivam Bhasin, Jakub Breier, Xiaolu Hou, Dirmanto Jap, Romain Poussier, Siang Meng Sim. This work is licensed under a Creative Commons Attribution 4.0 International License.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:TL Journal Articles

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