Paper 2024/272
Deep Learning Based Analysis of Key Scheduling Algorithm of Advanced Ciphers
Abstract
The advancements in information technology have made the Advanced Encryption Standard (AES) and the PRESENT cipher indispensable in ensuring data security and facilitating private transactions. AES is renowned for its flexibility and widespread use in various fields, while the PRESENT cipher excels in lightweight cryptographic situations. This paper delves into a dual examination of the Key Scheduling Algorithms (KSAs) of AES and the PRESENT cipher, which play a crucial role in generating round keys for their respective encryption techniques. By implementing deep learning methods, particularly a Neural Network model, our study aims to unravel the complexities of these KSAs and shed light on their inner workings.
Metadata
- Available format(s)
- Category
- Attacks and cryptanalysis
- Publication info
- Preprint.
- Keywords
- AESPRESENTDeep LearningNeural NetworkKey Scheduling Algorithm
- Contact author(s)
-
narendra k91630 @ gmail com
hemraj lamkuche @ gmail com - History
- 2024-02-26: revised
- 2024-02-18: received
- See all versions
- Short URL
- https://ia.cr/2024/272
- License
-
CC0
BibTeX
@misc{cryptoeprint:2024/272, author = {Narendra Kumar Patel and Hemraj Shobharam Lamkuche}, title = {Deep Learning Based Analysis of Key Scheduling Algorithm of Advanced Ciphers}, howpublished = {Cryptology {ePrint} Archive, Paper 2024/272}, year = {2024}, url = {https://eprint.iacr.org/2024/272} }