article · 2024
TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model
Jayati Dutta, Priyanka Peri, Rohith Malkuchi
Cited by 1Abstract and details only
Abstract
The rapid evolution of wireless communication technologies is epitomized by the advent of 5G-Advanced and the forthcoming 6G era. While 5G-Advanced enhances existing capabilities, 6G aims to seamlessly integrate AI-driven intelligence and sophisticated cryptographic techniques, significantly bolstering security. This paper explores the ZUC-PRN model [1], a neural network-based cipher inspired by the ZUC algorithm, proposed for enhancing wireless security in 5G and 6G networks. While ZUC-PRN shows potential for replacing traditional FSM-based ciphers, its resilience against various attacks remains unverified. We analyze its vulnerabilities to Slide and Time-Memory-Data Tradeoff (TMDT) attacks and assess its computational complexity, comparing it with the standard ZUC stream cipher. This study provides critical insights into the security and efficiency of the ZUC-PRN model, contributing to the development of more robust encryption methods for next-generation communication systems.
Cite this paper
Dutta, J., Peri, P., & Malkuchi, R. (2024). TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model. https://doi.org/10.1109/ants63515.2024.10898913
Dutta, Jayati, et al. “TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model.” 2024, pp. 1–6, https://doi.org/10.1109/ants63515.2024.10898913.
Dutta, Jayati, Priyanka Peri, and Rohith Malkuchi. 2024. “TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model.” https://doi.org/10.1109/ants63515.2024.10898913.
Dutta, J., Peri, P. and Malkuchi, R. (2024) ‘TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model’. Available at: https://doi.org/10.1109/ants63515.2024.10898913.
@article{dutta2024tradeoff,
title = {{TMD-Tradeoff and Slide Attack Analysis on the Novel ZUC-PRN Model}},
author = {Dutta, Jayati and Peri, Priyanka and Malkuchi, Rohith},
pages = {1--6},
year = {2024},
doi = {10.1109/ants63515.2024.10898913}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.