TY - GEN
T1 - Cross-Correlation Based Trace Segmentation for Clustering Power Analysis on Public Key Cryptosystems
AU - Hu, Yaoyuan
AU - Wang, An
AU - Gong, Weiping
AU - Wu, Jingjie
AU - Wang, Ziyu
AU - Zhang, Shiming
AU - Ma, Shufan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Simple Power Analysis (SPA) is a technique that directly analyzes the power consumption information collected during the execution of cryptographic algorithms. It is primarily based on the fact that different key values in public key cryptosystems (PKC) correspond to distinct operations, reflected in the power traces, allowing for key recovery. Effective segmentation of the power trace significantly enhances the efficiency of SPA, reducing the difficulty of key retrieval. This paper introduces a semi-automated Cross-Correlation Based Trace Segmentation method. We experimentally validated the segmentation method in scenarios involving smart cards, USB keys, and microcontrollers simulating unmanned aerial vehicle cryptographic modules. The results demonstrate the method’s high effectiveness in segmenting power traces of PKC.
AB - Simple Power Analysis (SPA) is a technique that directly analyzes the power consumption information collected during the execution of cryptographic algorithms. It is primarily based on the fact that different key values in public key cryptosystems (PKC) correspond to distinct operations, reflected in the power traces, allowing for key recovery. Effective segmentation of the power trace significantly enhances the efficiency of SPA, reducing the difficulty of key retrieval. This paper introduces a semi-automated Cross-Correlation Based Trace Segmentation method. We experimentally validated the segmentation method in scenarios involving smart cards, USB keys, and microcontrollers simulating unmanned aerial vehicle cryptographic modules. The results demonstrate the method’s high effectiveness in segmenting power traces of PKC.
KW - Power trace segmentation
KW - Public key cryptosystems
KW - Side-channel analysis
KW - Simple power analysis
UR - http://www.scopus.com/inward/record.url?scp=85198481078&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-61486-6_21
DO - 10.1007/978-3-031-61486-6_21
M3 - Conference contribution
AN - SCOPUS:85198481078
SN - 9783031614859
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 359
EP - 375
BT - Applied Cryptography and Network Security Workshops - ACNS 2024 Satellite Workshops, AIBlock, AIHWS, AIoTS, SCI, AAC, SiMLA, LLE, and CIMSS, Proceedings
A2 - Andreoni, Martin
PB - Springer Science and Business Media Deutschland GmbH
T2 - Satellite Workshops held in parallel with the 22nd International Conference on Applied Cryptography and Network Security, ACNS 2024
Y2 - 5 March 2024 through 8 March 2024
ER -