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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 June 2024) | Viewed by 30180

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Dr. Kien Nguyen

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Guest Editor

Institute for Advanced Academic Research, Chiba University, 1-33, Yayoi-cho, Inage-ku, Chiba 263-8522, Japan
Interests: Internet of Things; network protocols; network softwarization; distributed ledger technology; wireless communication
Special Issues, Collections and Topics in MDPI journals

Dr. Xiaoyan Wang

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Guest Editor

Department of Electrical and Electronic Systems Engineering, College of Engineering, Ibaraki University, Hitachi city, Japan
Interests: wireless communication; wireless sensing; AI; security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) has improved various aspects of human lives, such as introducing smart homes, intelligent agriculture, manufacturing automation, etc. With the advent of 5G networks and IoT wireless technologies, according to Gartner’s forecast, there will be 41.6 billion IoT devices connected to the Internet worldwide by 2025. Moreover, the advancements in edge/fog computing and AI/machine learning technologies will promisingly handle and understand the massive data generated by IoT devices, opening up new IoT application opportunities. Additionally, the emerging blockchain/distributed ledger technologies may enhance IoT security and privacy and drive the peer-to-peer exchange market between IoT devices (e.g., using cryptocurrency). In this context, there is a demand for novel communication, security, and privacy paradigms aiming to reach the full potential of IoT. This Special Issue seeks original articles on recent advances, solutions, and new challenges in those IoT-related issues.

Potential topics include, but are not limited to:

New networking architectures for IoT;
New computing architectures for IoT;
Evaluation and model wireless communication in IoT;
Evaluation and model networking, transport protocols in IoT;
New security- and privacy-preserving mechanisms in IoT;
Blockchain/distributed ledger technologies in IoT;
Novel payment/micropayment methods in IoT;
Scalability, adaptability solutions for IoT;
New IoT applications toward Sustainable Development Goals (SDGs);
Trial testbeds, prototypes of IoT standards.

Dr. Kien Nguyen
Dr. Xiaoyan Wang
Guest Editors

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Published Papers (11 papers)

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Research

30 pages, 1213 KiB

Open AccessEditor’s ChoiceArticle

Secure PUF-Based Authentication Systems

by Naing Win Tun and Masahiro Mambo

Sensors 2024, 24(16), 5295; https://doi.org/10.3390/s24165295 - 15 Aug 2024

Cited by 6 | Viewed by 3866

Abstract

The Internet of Things faces significant security challenges, particularly in device authentication. Traditional methods of PUF-based authentication protocols do not fully address IoT’s unique security needs and resource constraints. Existing solutions like Identity-Based Encryption with Physically Unclonable Functions enhance security but still struggle with protecting data during transmission. We show a new protocol that leverages PUFs for device authentication by utilizing Paillier homomorphic encryption or the plaintext equality test to enhance security. Our approach involves encrypting both the challenge–response pairs (CRPs) using Paillier homomorphic encryption scheme or ElGamal encryption for plaintext equality testing scheme. The verifier does not need access to the plaintext CRPs to ensure that sensitive data remain encrypted at all times and our approach reduces the computational load on IoT devices. The encryption ensures that neither the challenge nor the response can be deciphered by potential adversaries who obtain them during the transmission. The homomorphic property of the Paillier scheme or plaintext equality testing scheme allows a verifier to verify device authenticity without decrypting the CRPs, preserving privacy and reducing the computational load on IoT devices. Such an approach to encrypting both elements of the CRP provides resistance against CRP disclosure, machine learning attacks, and impersonation attacks. We validate the scheme through security analysis against various attacks and evaluate its performance by analyzing the computational overhead and the communication overhead. Comparison of average computational and communication time demonstrates Paillier scheme achieves approximately 99% reduction while the plaintext equality test achieves approximately 94% reduction between them. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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21 pages, 1246 KiB

Open AccessArticle

Decentralised Global Service Discovery for the Internet of Things

by Ryan Kurte, Zoran Salcic and Kevin I-Kai Wang

Sensors 2024, 24(7), 2196; https://doi.org/10.3390/s24072196 - 29 Mar 2024

Cited by 2 | Viewed by 1418

Abstract

The Internet of Things (IoT) consists of millions of devices deployed over hundreds of thousands of different networks, providing an ever-expanding resource to improve our understanding of and interactions with the physical world. Global service discovery is key to realizing the opportunities of the IoT, spanning disparate networks and technologies to enable the sharing, discovery, and utilisation of services and data outside of the context in which they are deployed. In this paper, we present Decentralised Service Registries (DSRs), a novel trustworthy decentralised approach to global IoT service discovery and interaction, building on DSF-IoT to allow users to simply create and share public and private service registries, to register and query for relevant services, and to access both current and historical data published by the services they discover. In DSR, services are registered and discovered using signed objects that are cryptographically associated with the registry service, linked into a signature chain, and stored and queried for using a novel verifiable DHT overlay. In contrast to existing centralised and decentralised approaches, DSRs decouple registries from supporting infrastructure, provide privacy and multi-tenancy, and support the verification of registry entries and history, service information, and published data to mitigate risks of service impersonation or the alteration of data. This decentralised approach is demonstrated through the creation and use of a DSR to register and search for real-world IoT devices and their data as well as qualified using a scalable cluster-based testbench for the high-fidelity emulation of peer-to-peer applications. DSRs are evaluated against existing approaches, demonstrating the novelty and utility of DSR to address key IoT challenges and enable the sharing, discovery, and use of IoT services. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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41 pages, 13009 KiB

Open AccessArticle

Securing Cloud-Assisted Connected and Autonomous Vehicles: An In-Depth Threat Analysis and Risk Assessment

by Al Tariq Sheik, Carsten Maple, Gregory Epiphaniou and Mehrdad Dianati

Sensors 2024, 24(1), 241; https://doi.org/10.3390/s24010241 - 31 Dec 2023

Cited by 6 | Viewed by 3203

Abstract

As threat vectors and adversarial capabilities evolve, Cloud-Assisted Connected and Autonomous Vehicles (CCAVs) are becoming more vulnerable to cyberattacks. Several established threat analysis and risk assessment (TARA) methodologies are publicly available to address the evolving threat landscape. However, these methodologies inadequately capture the threat data of CCAVs, resulting in poorly defined threat boundaries or the reduced efficacy of the TARA. This is due to multiple factors, including complex hardware–software interactions, rapid technological advancements, outdated security frameworks, heterogeneous standards and protocols, and human errors in CCAV systems. To address these factors, this study begins by systematically evaluating TARA methods and applying the Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, and Elevation of privileges (STRIDE) threat model and Damage, Reproducibility, Exploitability, Affected Users, and Discoverability (DREAD) risk assessment to target system architectures. This study identifies vulnerabilities, quantifies risks, and methodically examines defined data processing components. In addition, this study offers an attack tree to delineate attack vectors and provides a novel defense taxonomy against identified risks. This article demonstrates the efficacy of the TARA in systematically capturing compromised security requirements, threats, limits, and associated risks with greater precision. By doing so, we further discuss the challenges in protecting hardware–software assets against multi-staged attacks due to emerging vulnerabilities. As a result, this research informs advanced threat analyses and risk management strategies for enhanced security engineering of cyberphysical CCAV systems. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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27 pages, 8494 KiB

Open AccessArticle

A Comprehensive Analysis: Evaluating Security Characteristics of Xbee Devices against Zigbee Protocol

by Vlad Gavra, Ovidiu A. Pop and Ionut Dobra

Sensors 2023, 23(21), 8736; https://doi.org/10.3390/s23218736 - 26 Oct 2023

Cited by 3 | Viewed by 1902

Abstract

In recent times, the security of sensor networks, especially in the field of IoT, has become a priority. This article focuses on the security features of the Zigbee protocol in Xbee devices developed by Digi International, specifically in the Xbee 3 (XB3-24) devices. Using the TI LaunchXL-CC26X2R1 kit, we intercepted and analyzed packets in real-time using the Wireshark application. The study encompasses various stages of network formation, packet transmission and analysis of security key usage, considering scenarios as follows: without security, distributed security mode and centralized security mode. Our findings highlight the differences in security features of Xbee devices compared to the Zigbee protocol, validating and invalidating methods of establishing security keys, vulnerabilities, strengths, and recommended security measures. We also discovered that security features of the Xbee 3 devices are built around a global link key preconfigured therefore constituting a vulnerability, making those devices suitable for man-in-the-middle and reply attacks. This work not only elucidates the complexities of Zigbee security in Xbee devices but also provides direction for future research for authentication methods using asymmetric encryption algorithms such as digital signature based on RSA and ECDSA. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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16 pages, 2632 KiB

Open AccessArticle

Non-Fungible Tokens Based on ERC-4519 for the Rental of Smart Homes

by Javier Arcenegui, Rosario Arjona and Iluminada Baturone

Sensors 2023, 23(16), 7101; https://doi.org/10.3390/s23167101 - 11 Aug 2023

Viewed by 2481

Abstract

The rental of houses is a common economic activity. However, there are many inconveniences that arise when renting a property. The lack of trust between the landlord and the tenant due to fraud or squatters makes it necessary to involve third parties to minimize risk. A blockchain (such as Ethereum) provides an ideal solution to act as a low-cost intermediary. This paper proposes the use of non-fungible tokens (NFTs) based on ERC-4519 for smart home tokenization. The ERC-4519 is an Ethereum standard for describing NFTs tied to physical assets, allowing smart homes (assets) to be linked to NFTs so that the smart homes can interact with the blockchain and perform transactions, know their landlord (owner) and assigned tenant (user), whether they are authenticated or not, and know their operating mode (NFT state). The payments associated with the rental process are made using the NFT, eliminating the need for additional fungible tokens and simplifying the process. The entire rental process is described and illustrated with a proof of concept using a Pycom Wipy 3.0 as a smart home gateway and a smart contract programmed in Solidity, which is deployed on the Goerli Testnet for Ethereum. Experimental results show that the smart home gateway takes a few tens of milliseconds to complete a transaction, and the transaction costs of the relevant functions of the smart contract are quite affordable. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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31 pages, 575 KiB

Open AccessArticle

Guidance Framework for Developing IoT-Enabled Systems’ Cybersecurity

by Hezam Akram Abdulghani, Anastasija Collen and Niels Alexander Nijdam

Sensors 2023, 23(8), 4174; https://doi.org/10.3390/s23084174 - 21 Apr 2023

Cited by 6 | Viewed by 3593

Abstract

Internet of Things (IoT) faces security concerns different from existing challenges in conventional information systems connected through the Internet because of their limited resources and heterogeneous network setups. This work proposes a novel framework for securing IoT objects, the key objective of which is to assign different Security Level Certificates (SLC) for IoT objects according to their hardware capabilities and protection measures implemented. Objects with SLCs, therefore, will be able to communicate with each other or with the Internet in a secure manner. The proposed framework is composed of five phases, namely: classification, mitigation guidelines, SLC assignment, communication plan, and legacy integration. The groundwork relies on the identification of a set of security attributes, termed security goals. By performing an analysis on common IoT attacks, we identify which of these security goals are violated for specific types of IoT. The feasibility and application of the proposed framework is illustrated at each phase using the smart home as a case study. We also provide qualitative arguments to demonstrate how the deployment of our framework solves IoT specific security challenges. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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19 pages, 359 KiB

Open AccessArticle

VORTEX: Network-Driven Opportunistic Routing for Ad Hoc Networks

by Ryo Yamamoto, Taku Yamazaki and Satoshi Ohzahata

Sensors 2023, 23(6), 2893; https://doi.org/10.3390/s23062893 - 7 Mar 2023

Cited by 2 | Viewed by 2013

Abstract

The potential of ad hoc networks, which enable flexible and dynamic network establishment only by mobile terminals equipped with wireless communication devices, has recently attracted attention for the coming IoT era. Although the nature of ad hoc networks shows the advantages of their autonomous and distributed network management, a manifestation of drawbacks owing to the nature of wireless communication and the mobility of terminals are inevitable. Many routing protocols have already been proposed to address the issues by adapting to nature and achieving a certain level of improvement. However, the routing protocols still suffer from difficulties in information collection for routing and adaptive route management during communication. Moreover, there is another issue that end pair-based routing procedures prevent other end pairs from reusing the routing information effectively. To address the drawbacks of conventional routing protocols, this paper proposes VORTEX, a novel routing protocol that employs an opportunistic routing strategy using hierarchization. One of the characteristic features of VORTEX is its network-driven opportunistic forwarding, in which packets travel toward destination terminals using hierarchy as a guide without conventional route discovery procedures. Moreover, another characteristic feature of VORTEX is that the hierarchical structure also contributes to adapting to communication environment changes in an autonomous manner. In other words, VORTEX enables flexible network-wide information-based routing only with the locally collected information. The simulation results show that the proposed VORTEX could provide better service quality and reliability with improved efficiency compared to the conventional routing protocols. Furthermore, the most significant contribution is not only in the communication performance but also VORTEX omits route discovery or route maintenance from routing protocols, and formed networks themselves have a function to deliver packets toward destination terminals. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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16 pages, 836 KiB

Open AccessArticle

Simulating IoT Workflows in DISSECT-CF-Fog

by Andras Markus, Ali Al-Haboobi, Gabor Kecskemeti and Attila Kertesz

Sensors 2023, 23(3), 1294; https://doi.org/10.3390/s23031294 - 23 Jan 2023

Cited by 3 | Viewed by 2625

Abstract

The modelling of IoT applications utilising the resources of cloud and fog computing is not straightforward because they have to support various trigger-based events that make human life easier. The sequence of tasks, such as performing a service call, receiving a data packet in the form of a message sent by an IoT device, and managing actuators or executing a computational task on a virtual machine, are often associated with and composed of IoT workflows. The development and deployment of such IoT workflows and their management systems in real life, including communication and network operations, can be complicated due to high operation costs and access limitations. Therefore, simulation solutions are often applied for such purposes. In this paper, we introduce a novel simulator extension of the DISSECT-CF-Fog simulator that leverages the workflow scheduling and its execution capabilities to model real-life IoT use cases. We also show that state-of-the-art simulators typically omit the IoT factor in the case of the scientific workflow evaluation. Therefore, we present a scalability study focusing on scientific workflows and on the interoperability of scientific and IoT workflows in DISSECT-CF-Fog. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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16 pages, 7288 KiB

Open AccessArticle

mmSafe: A Voice Security Verification System Based on Millimeter-Wave Radar

by Zhanjun Hao, Jianxiang Peng, Xiaochao Dang, Hao Yan and Ruidong Wang

Sensors 2022, 22(23), 9309; https://doi.org/10.3390/s22239309 - 29 Nov 2022

Cited by 2 | Viewed by 2593

Abstract

With the increasing popularity of smart devices, users can control their mobile phones, TVs, cars, and smart furniture by using voice assistants, but voice assistants are susceptible to intrusion by outsider speakers or playback attacks. In order to address this security issue, a millimeter-wave radar-based voice security authentication system is proposed in this paper. First, the speaker’s fine-grained vocal cord vibration signal is extracted by eliminating static object clutter and motion effects; second, the weighted Mel Frequency Cepstrum Coefficients (MFCCs) are obtained as biometric features; and finally, text-independent security authentication is performed by the WMHS (Weighted MFCCs and Hog-based SVM) method. This system is highly adaptable and can authenticate designated speakers, resist intrusion by other unspecified speakers as well as playback attacks, and is secure for smart devices. Extensive experiments have verified that the system achieves a 93.4% speaker verification accuracy and a 5.8% miss detection rate for playback attacks. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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17 pages, 1453 KiB

Open AccessArticle

Towards Developing a Robust Intrusion Detection Model Using Hadoop–Spark and Data Augmentation for IoT Networks

by Ricardo Alejandro Manzano Sanchez, Marzia Zaman, Nishith Goel, Kshirasagar Naik and Rohit Joshi

Sensors 2022, 22(20), 7726; https://doi.org/10.3390/s22207726 - 12 Oct 2022

Cited by 5 | Viewed by 2415

Abstract

In recent years, anomaly detection and machine learning for intrusion detection systems have been used to detect anomalies on Internet of Things networks. These systems rely on machine and deep learning to improve the detection accuracy. However, the robustness of the model depends on the number of datasamples available, quality of the data, and the distribution of the data classes. In the present paper, we focused specifically on the amount of data and class imbalanced since both parameters are key in IoT due to the fact that network traffic is increasing exponentially. For this reason, we propose a framework that uses a big data methodology with Hadoop–Spark to train and test multi-class and binary classification with one-vs-rest strategy for intrusion detection using the entire BoT IoT dataset. Thus, we evaluate all the algorithms available in Hadoop–Spark in terms of accuracy and processing time. In addition, since the BoT IoT dataset used is highly imbalanced, we also improve the accuracy for detecting minority classes by generating more datasamples using a Conditional Tabular Generative Adversarial Network (CTGAN). In general, our proposed model outperforms other published models including our previous model. Using our proposed methodology, the F1-score of one of the minority class, i.e., Theft attack was improved from 42% to 99%. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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16 pages, 1527 KiB

Open AccessArticle

A Usage Aware Dynamic Spectrum Access Scheme for Interweave Cognitive Radio Network by Exploiting Deep Reinforcement Learning

by Xiaoyan Wang, Yuto Teraki, Masahiro Umehira, Hao Zhou and Yusheng Ji

Sensors 2022, 22(18), 6949; https://doi.org/10.3390/s22186949 - 14 Sep 2022

Cited by 6 | Viewed by 2231

Abstract

Future-generation wireless networks should accommodate surging growth in mobile data traffic and support an increasingly high density of wireless devices. Consequently, as the demand for spectrum continues to skyrocket, a severe shortage of spectrum resources for wireless networks will reach unprecedented levels of challenge in the near future. To deal with the emerging spectrum-shortage problem, dynamic spectrum access techniques have attracted a great deal of attention in both academia and industry. By exploiting the cognitive radio techniques, secondary users (SUs) are capable of accessing the underutilized spectrum holes of the primary users (PUs) to increase the whole system’s spectral efficiency with minimum interference violations. In this paper, we mathematically formulate the spectrum access problem for interweave cognitive radio networks, and propose a usage-aware deep reinforcement learning based scheme to solve it, which exploits the historical channel usage data to learn the time correlation and channel correlation of the PU channels. We evaluated the performance of the proposed approach by extensive simulations in both uncorrelated and correlated PU channel usage cases. The evaluation results validate the superiority of the proposed scheme in terms of channel access success probability and SU-PU interference probability, by comparing it with ideal results and existing methods. Full article

(This article belongs to the Special Issue Communication, Security, and Privacy in IoT)

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