Statistical Fault Analysis of the Simeck Lightweight Cipher in the Ubiquitous Sensor Networks

9Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

With the development of wireless technology, the ubiquitous sensor networks have a profound effect on the way human interacts with computers, devices and environment. In order to reduce the potentially serious risks in the interaction, applying lightweight ciphers is effective to balance security, efficiency and convenience. Simeck is such a lightweight cipher that provides data confidentiality, authentication and integrity. It is significant to explore whether Simeck remains robust security. Up to now, the attacking assumptions of the previous security analysis of Simeck focus on the known-plaintext attack and the chosen-plaintext attack. There is no literature about Simeck against the ciphertext-only attack, which represents the weakest attacking capability of the attackers. On the assumption of the ciphertext-only attack, this paper proposes the security analysis of Simeck against the statistical fault analysis with a series of novel distinguishers of KDE, MME and MME-GF. The experimental results show that the proposed distinguishers can recover the secret key of Simeck in both decreasing faults and increasing reliability and accuracy. Thus, Simeck cannot resist against the statistical fault analysis with the proposed distinguishers. Furthermore, the good performance of these novel distinguishers can be applied on the PRESENT lightweight cipher. It offers the valuable reference for the design and analysis of the lightweight ciphers in the ubiquitous sensor networks.

Cite

CITATION STYLE

APA

Li, W., Li, J., Gu, D., Li, C., & Cai, T. (2021). Statistical Fault Analysis of the Simeck Lightweight Cipher in the Ubiquitous Sensor Networks. IEEE Transactions on Information Forensics and Security, 16, 4224–4233. https://doi.org/10.1109/TIFS.2021.3102485

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free