The Internet of Things (IoT) revolution leads to a range of critical services which rely on IoT devices. Nevertheless, they often lack proper security, becoming the gateway to attack the whole system. IoT security protocols often rely on stream ciphers, where pseudo-random number generators (PRNGs) are an essential part of them. In this article, a family of ciphers with strong characteristics that make them difficult to be analyzed by standard methods is described. In addition, we will discuss an innovative technique of sequence decomposition and present a novel algorithm to evaluate the strength of binary sequences, a key part of the IoT security stack. The density of the binomial sequences in the decomposition has been studied experimentally to compare the performance of the presented algorithm with previous works.
The ubiquity of smart devices and IoT are the main forces behind the development of cryptographic primitives that preserve the security of this devices, with the resources constraints they face. In this sense, the development of lightweight cryptographic algorithms, where PRNGs are an essential part of them, provides security to all these interconnected devices. In this work, a family of sequence generators with hard characteristics to be analyzed by standard methods is described. Moreover, we introduce an innovative technique for sequence decomposition that allows one to extract useful information on the sequences under study. In addition, diverse algorithms to evaluate the strength of such binary sequences have been introduced and analyzed to show which performs better.
A simple algorithm to compute the linear complexity of binary sequences with period a power of 2 has been proposed. The algorithm exploits the fractal structure of the binomial representation in this kind of binary sequences. The application of the general algorithm to a particular family of cryptographic sequences (generalized sequences) improves its performance as decreases the amount of sequence to be processed.
The Internet of Things (IoT) revolution leads to a range of critical services which rely on IoT devices. Nevertheless, they often lack proper security, becoming the gateway to attack the whole system. IoT security protocols often rely on stream ciphers, where pseudo-random number generators (PRNGs) are an essential part of them. In this article, a family of ciphers with strong characteristics that make them difficult to be analyzed by standard methods is described. In addition, we will discuss an innovative technique of sequence decomposition and present a novel algorithm to evaluate the strength of binary sequences, a key part of the IoT security stack. The density of the binomial sequences in the decomposition has been studied experimentally to compare the performance of the presented algorithm with previous works.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.