A lightweight hierarchical authentication scheme for internet of things

Akbarzadeh, Aida; Bayat, Majid; Zahednejad, Behnam; Payandeh, Ali; Aref, Mohammad Reza

doi:10.1007/s12652-018-0937-6

Cited by 18 publications

(5 citation statements)

References 41 publications

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“…They also compared the performance and privacy of their suggested technique to those of current solutions. Compared to alternative methods, the results demonstrated the suggested scheme's efficacy and safety [20].…”

Section: The Related Workmentioning

confidence: 86%

Lightweight Authentication Enhancement Using Arnold Chaotic Map and Markov-Chain for Internet of Things Applications

2023

IJIES

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The Internet of Things (IoT) was a new concept that connected various physical things to the internet. The IoT is fast expanding and will soon significantly impact everyday life. Although the increasing number of connected IoT devices is simplifying life, they risk our data. Radiofrequency identification (RFID) assists in the automated identification of connected IoT devices. Furthermore, the primary challenges for RFID tag-connected technology are privacy and security. With the improving safety of solutions RFID for many apps, RFID necessitates a centralized database widening. Blockchain techniques are speedily establishing themselves together as a new distributed and decentralized replacement. And it provides enhanced transparency, data security, immutability, dependability, and lower maintenance costs. Because of its inherent benefits, RFID is projected to play a significant part in enabling identifying technology on the IoT. However, due to its association with sensor technology, it has the potential to be applied in a wide range of industries. Security, however, is one of the more complex components of creating an RFID system. RFID Security focuses around authentication and privacy concerns. From the previous works, we found that the computing cost and uptime are higher. To solve these problems, we offer improving lightweight authentication using Arnold Chaotic map and Markov chain for IoT applications. The proposed method uses random algorithms (Markova chain, Arnold map chaotic, and ECC), which add high security. We also used blockchain technology to transfer keys through a non-security channel. Based on parameters such as (communication cost, throughput rate, storage requirements, transmission delay, and computational cost) the results of the proposed RFID protocol were compared with several RFID-based security solutions. As a result, the proposed lightweight scheme is more efficient and secure than existing RFID systems in terms of performance, according to simulation results, and is fully compatible with actual applications.

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Section: The Related Workmentioning

confidence: 86%

Lightweight Authentication Enhancement Using Arnold Chaotic Map and Markov-Chain for Internet of Things Applications

2023

IJIES

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“…They are widely used to provide confidentiality by encrypting large amounts of data, either locally or over network communication. Recently, more research has been done on the design of lightweight cryptographic (LWC) schemes which are suitable for resource-constrained devices in applications, such as the Internet of Things, 30,31 cloud computing, 32,33 healthcare, and mobile networks. 34 Given their extensive usage, it is crucial to evaluate the security of block ciphers, and especially lightweight ciphers in the LWC domain.…”

Section: Motivationmentioning

confidence: 99%

An improved integral distinguisher scheme based on neural networks

Zahednejad

Lyu

2022

Int J of Intelligent Sys

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At CRYPTO 2019, A. Gohr made a breakthrough in combining classical cryptanalysis and deep learning and applied his method to round reduced SPECK successfully. However, his suggested neural-based distinguisher scheme is only limited to differential cryptanalysis. In this paper, we have the following contributions:1. We combine integral cryptanalysis and deep learning to propose our neural-based integral distinguisher scheme for the first time. To illustrate the effectiveness of our distinguisher scheme, we apply it to block ciphers of different structures, such as substitution-permutation structure ciphers (PRESENT and RECTANGLE), Feistel structure cipher (LBLOCK), and addrotate-XOR cipher (SPECK) and compare the results with the state-of-the-art classical integral distinguishing method, namely, the bit-based division property. To our great surprise, our neural network-based integral distinguisher can extend the number of distinguished rounds for all block ciphers by two additional rounds (except RECTANGLE, where it is improved by one round) under the same data complexity.2. As an additional advantage of our scheme, we demonstrate that our Neural Distinguisher (ND) is not only helpful for block cipher designers but

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“…Internet of ings (IoT) is a next-generation information network that integrates the radio frequency identification technology and sensor technology based on induction equipment into the Internet. Hierarchical sharing technology of information resources has become a hot topic in the research of the Internet of ings [6,7], which enables items' information to be accurately, safely, and efficiently located and queried. At present, the Internet of things and the underlying information resources information resources sharing layering technology research mainly focuses on two basic aspects: one is about the Internet of things RFID Savant middleware [8], hierarchy, found [9,10] RFID information service, trusted query mechanism [11], and the Internet information resources in the center of the recognition named or information resources sharing layered model [12]; the underlying technologies such as research put forward is the most representative of Internet information resources sharing layered model; the second is the research on the trust-driven management and scheduling algorithm of Internet resources or cloud resources [13].…”

Section: Related Workmentioning

confidence: 99%

Cloud Trust-Driven Hierarchical Sharing Method of Internet of Things Information Resources

Zhang

2021

Complexity

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Short information sharing time is one of the problems to be solved in the traditional Internet. Therefore, this paper proposes a hierarchical simulation of the Internet of Things sharing structure framework that trusts the cloud to drive Internet information resource sharing. By setting thresholds and iterative adjustment parameters, a complementary judgment matrix is constructed to obtain the minimum nonnegative deviation value and the optimal weight vector. This paper sorts according to the value of the Internet information security model, obtains the optimal model to avoid human tampering, and designs the information resource acquisition process to ensure the reliability of the source data. We use radio frequency identification (RFID) equipment in the preprocessing of massive heterogeneous data in the Internet of Things. In a network environment where resources are limited and heterogeneous are fully considered, the trust-based adaptive detection algorithm is used to evaluate the credibility of the trust-driven algorithm for hierarchical information resource sharing services in the cloud environment of the Internet of Things. We propose a cloud trust-driven hierarchical information resource sharing Internet information resource model. Firstly, the key characteristics of hierarchical information resource sharing are analyzed. Then, a hierarchical information resource sharing model was established by using specific constraints, trust steepness function, cloud trust evaluation criteria, and trust constraint coefficient. Finally, an example of IoT system is designed to verify the effectiveness of the model. Experimental results show that, compared with the traditional model or algorithm, this model has a good hierarchical sharing effect of the underlying resource information.

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A lightweight hierarchical authentication scheme for internet of things

Cited by 18 publications

References 41 publications

Lightweight Authentication Enhancement Using Arnold Chaotic Map and Markov-Chain for Internet of Things Applications

Lightweight Authentication Enhancement Using Arnold Chaotic Map and Markov-Chain for Internet of Things Applications

An improved integral distinguisher scheme based on neural networks

Cloud Trust-Driven Hierarchical Sharing Method of Internet of Things Information Resources

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