.png){kind=icon}
.png){kind=icon}
Return
A generic framework for decomposing block cipher structure with secret components
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jisa.2021.102855.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we present a generic framework for decomposing block cipher structure with secret components. The generic framework is based on the zero-correlation linear cryptanalysis and exploits clusters of zero correlation linear hulls to establish a system of equations to recover the secret components. In order to solve such a system, we convert the operations into the field of real numbers. By utilizing the coordinate partition technique, both the time and data complexity will be mitigated to make the framework more competitive. We apply the framework to the Feistel structure with SP-type round functions and both the attack rounds and complexity perform better than previous results. Finally, we apply the proposed framework to the Type-1 Feistel structure to demonstrate its generality and improve the previous results against such structure. Our work provides further insights into the security of block cipher structure with secret components.
Keywords:
Cryptanalysis
Block cipher structure
Decomposition
Secret component
Zero-correlation linear hull
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.7
Papers:
1.9K
Citations:
4.9K