A Tutorial on Next Generation Heterogeneous IoT Networks and Node Authentication

Sood, Keshav; Yu, Shui; Nguyen, Dinh Duc Nha; Xiang, Yong; Feng, Bohao; Zhang, Xiaoning

doi:10.1109/iotm.001.2100115

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…However, neither QKD nor CRKG provides a means to authenticate the transmission source. Therefore, source authentication in CR-QKD should be further studied by using asymmetric cryptography techniques or emerging physicallayer techniques, such as radio frequency fingerprinting identification and physical unclonable function [1]. • Untrusted QAPs: The proposed CR-QKD scheme relies on the trust of the intermediate QAPs.…”

Section: Discussionmentioning

confidence: 99%

“…The CR-QKD protocol comprises three main phases, i.e, QKD 1 , CRKG and edge forwarding, which will be elaborated below.…”

Section: A Mechanism Descriptionmentioning

confidence: 99%

“…The flourish of IoT, however, has resulted in the generation of a substantial amount of private messages exchanged over public channels, which has grabbed one's attention. Unfortunately, IoT devices are susceptible to various threats and security challenges, which pose hazards for the advancement of IoT in sensitive fields, such as smart homes, unmanned vehicles, e-health, and military networks [1]. In order to avoid being revealed to a third party, a message is usually encrypted using a secret key shared among the communicating devices.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Information-Theoretic Secure Key Sharing for Wide-Area Mobile Applications

Li¹,

Luo²,

Yu³

et al. 2024

IEEE Wireless Commun.

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With the rapid growth of handheld devices in the internet of things (IoT) networks, mobile applications have become ubiquitous in everyday life. As technology is developed, so do also the risks and threats associated with it, especially in the forthcoming quantum era. Existing IoT networks, however, lack a quantum-resistant secret key sharing scheme to meet confidential message transmission demands in wide-area mobile applications. To address this issue, this article proposes a new scheme, channel reciprocity (CR) based quantum key distribution (QKD) CR-QKD, which accomplishes the goal of secret key sharing by combining emerging techniques of QKD and CR-based key generation (CRKG). Exploiting laws of quantum physics and properties of wireless channels, the proposed scheme is able to ensure the secrecy of the key, even against computationally unbounded adversaries. The basic mechanism is elaborated for a single-user case and it is extended into a multi-user case by redesigning a multi-user edge forwarding strategy. In addition, to make CR-QKD more practical, some enhancement strategies are studied to reduce the time delay and to improve the secret key generation rate in a secure manner. A prototype of CR-QKD is demonstrated in a metropolitan area network, where secret keys are shared between two remote IoT devices that are roughly fifteen kilometers apart from each other. The experimental results have verified that CR-QKD allows a secret key rate of 424 bits per second with a retransmission rate of 2.1%.

show abstract

Section: Discussionmentioning

confidence: 99%

“…The CR-QKD protocol comprises three main phases, i.e, QKD 1 , CRKG and edge forwarding, which will be elaborated below.…”

Section: A Mechanism Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Information-Theoretic Secure Key Sharing for Wide-Area Mobile Applications

Li¹,

Luo²,

Yu³

et al. 2024

IEEE Wireless Commun.

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show abstract

“…To address this issue, the authors have proposed a novel approach by leveraging the first layer (physical layer) in the authentication process and incorporating ML algorithms to assist with authentication. This innovative solution offers advantages such as reduced synchronization and acknowledgement requirements, leading to node energy savings [128]. However, one of the unresolved concerns is the privacy condition.…”

Section: Privacy Concernsmentioning

confidence: 99%

Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review

Ghadi,

Mazhar,

Shloul

et al. 2024

IEEE Access

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Energy efficiency and safety are two essential factors that play a significant role in operating a wireless sensor network. However, it is claimed that these two factors are naturally conflicting. The level of electrical consumption required by a security system is directly proportional to its degree of complexity. Wireless sensor networks require additional security measures above the capabilities of conventional network security protocols, such as encryption and key management. The potential application of machine learning techniques to address network security concerns is frequently discussed. These devices will have complete artificial intelligence capabilities, enabling them to understand their environment and respond. During the training phase, machine-learning systems may face challenges due to the large amount of data required and the complex nature of the training procedure. This article focuses on machine learning algorithms used to solve the security issues of wireless sensor networks. This article also focuses on different types of attacks on layers of the wireless sensor network. Moreover, this study addresses several unsolved issues, including adapting machine learning algorithms to accommodate the sensors' functionalities in this network configuration. Furthermore, this article also focuses on open issues in this field that must be solved.

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“…Solutions in using 5G and other networks (e.g., Wi-Fi). Bhuyan et al, 2021;Ksentini and Frangoudis, 2020;Gonzalez et al, 2020;Liyanage et al, 2018;Wang and Yan, 2015;Tahir et al, 2020;Azzaoui et al, 2020;Nieto et al, 2017Nieto et al, , 2018Zhang and Lin, 2017;Compagno et al, 2017;Dik and Berger, 2021;Benzaid and Taleb, 2020;Zhao et al, 2021a;Bitsikas and Pöpper, 2021;Chaudhary et al, 2020;Gao et al, 2021;Sood et al, 2021;Cao et al, 2020;Ding et al, 2022b;Wu et al, 2018;Shi and Sagduyu, 2021;Sullivan et al, 2021;Mei et al, 2018;Gebremariam et al, 2021;Ginzboorg and Niemi, 2016;Rotinsulu and Fitri Sari, 2018;Vassilakis et al, 2017;Ar-joune and Faruque, 2020]. An adversary can maliciously (1) use legitimate orchestrator access to manipulate the configuration and run a compromised network function, (2) take advantage of malicious insiders attacks, (3) perform unauthorized access (e.g., to confidential data [Isaksson and Norrman, 2020] and to RFID tags [Rahimi et al, 2018]), (4) tampering, (5) perform resource exhaustion, (6) turn services unavailable, ( 7) analyze or modify traffic, (8) perform data leakage (e.g., capturing valuable personal information [Bordel et al, 2021;Annessi et al, 2018;Vreman and Maggio, 2019]), (…”

Section: Item Description Item Descriptionmentioning

confidence: 99%

A Systematic Literature Mapping on the Security of 5G and Vertical Applications

Sobrinho,

Santos,

Silva

et al. 2023

Preprint

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The deployment of 5G infrastructure is one of the main vectors for new application scenarios since it enables enhanced data bandwidth, low latency, and comprehensive signal coverage. As a result, this communication system supports various vertical applications such as the Industrial Internet of Things, smart health, smart cities, smart grids, and transportation systems. However, these applications bring new challenges to 5G networks due to specific requirements for such scenarios. Furthermore, as software-based technologies, including network slicing, software-defined networks, network function virtualization, and multi-access edge computing are a fundamental part of the 5G architecture, the network can expose these applications to new security and privacy concerns. This study summarizes the existing literature on 5G vertical applications security. We highlight vulnerabilities, threats, attacks, and solutions for 5G vertical applications. We conducted a Systematic Literature Mapping (SLM) to discuss security and privacy challenges regarding the 5G vertical applications. The SLM answered the following research question: what is the state-of-the-art regarding security in 5G networks and vertical applications? We reviewed 389 papers from 2,349 produced by searching with a curated search query and discussed vulnerabilities, threats, attacks, and solutions for 5G vertical applications. Smart cities, Industry 4.0, smart transportation, public services, smart grids, and smart health are vertical applications with relevant security concerns. We observed the need for more research since the 5G and vertical applications continuously evolve. This review also uncovers research gaps and future research directions.

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A Tutorial on Next Generation Heterogeneous IoT Networks and Node Authentication

Cited by 10 publications

References 11 publications

Information-Theoretic Secure Key Sharing for Wide-Area Mobile Applications

Information-Theoretic Secure Key Sharing for Wide-Area Mobile Applications

Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review

A Systematic Literature Mapping on the Security of 5G and Vertical Applications

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