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Electronics
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Precise Timing and Security in Internet of Things
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Precise Timing and Security in Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 4213

Special Issue Editors

Dr. Xintao Huan

E-Mail Website
Guest Editor
School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Interests: wireless security; time synchronization; Internet of Things; wireless sensor network
Prof. Dr. Heng Wang

E-Mail Website
Guest Editor
Key Laboratory of Industrial Internet of Things and Networked Control, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Interests: industrial Internet of Things; wireless sensor networks; clock synchronization; real-time scheduling
Special Issues, Collections and Topics in MDPI journals
Dr. Yan Zong

E-Mail Website
Guest Editor
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: wireless networked control; machine learning; their applications to aerial swarms and Internet of Things
Dr. Guyue Li

E-Mail Website
Guest Editor
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
Interests: Physical Layer Security; Wireless Communication Security
Dr. Chuan Zhang

E-Mail Website
Guest Editor
School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Interests: applied cryptography; mobile crowdsourcing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) has revolutionized every aspect of the current world, including home, healthcare, transportation, and industry, where now billions of IoT devices connect massive space–air–ground physical objects to the Internet. Laying its foundation on diverse wireless technologies such as wireless sensor networks, low-power wide-area network, wireless local area network, and aerial networking, IoT derives different applications that specialize in long-range, long-term, and also large-scale applications. A fundamental service demanded by IoT is timing. On the one hand, it supports basic data ordering and event detection for local IoT devices; on the other hand, it serves as the cornerstone for network-level collaboration. Security is as vital to IoT as timing, if not more so. More and more IoT devices have been deployed in critical areas, whose security becomes the first line of defense for crucial data and contents.

State-of-the-art research on IoT timing and security have attracted great interest in precise timing and endogens security; achieving the former requires new time synchronization concepts, while achieving the latter poses new demands on security measures such as identification and key generation. However, IoT devices’ limited computing and power resources pose further constraints on the development of their timing and security. Chasing timing and security shall simultaneously consider their energy consumption and computational complexity, as well as their robustness and sustainability.

The objective of this Special Issue is to explore the recent advances in precise timing and security in the area of Internet of Things. We invite high-quality original research and review articles in this area for submission. Potential topics include, but are not limited to, the following:

  • Time synchronization concepts tailored for IoT;
  • Centralized and distributed time synchronization mechanisms for IoT;
  • Theoretical time synchronization methods for IoT;
  • Synchronization solutions for aerial IoT such as aerial swarms;
  • Application of time synchronization in IoT;
  • Experimental studies and practical time synchronization results for IoT;
  • Design of novel security measures for IoT;
  • Cyber attacks and their defenses for IoT;
  • Radio frequency fingerprinting identification technologies for IoT;
  • Hardware fingerprinting identification technologies for IoT;
  • Wireless key generation methods for IoT.

Dr. Xintao Huan
Prof. Dr. Heng Wang
Dr. Yan Zong
Dr. Guyue Li
Dr. Chuan Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Internet of Things
  • time synchronization
  • cybersecurity
  • radio frequency fingerprinting
  • hardware fingerprinting
  • wireless key generation

Published Papers (6 papers)

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Research

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17 pages, 15461 KiB  
Article
Design and Evaluation of Device Authentication and Secure Communication System with PQC for AIoT Environments
by Yu-Jen Chen, Chien-Lung Hsu, Tzu-Wei Lin and Jung-San Lee
Electronics 2024, 13(8), 1575; https://doi.org/10.3390/electronics13081575 - 20 Apr 2024
Viewed by 274
Abstract
With the rapid development of Internet of Things (IoT) technology, the number of IoT users is growing year after year. IoT will become a part of our daily lives, so it is likely that the security of these devices will be an important [...] Read more.
With the rapid development of Internet of Things (IoT) technology, the number of IoT users is growing year after year. IoT will become a part of our daily lives, so it is likely that the security of these devices will be an important issue in the future. Quantum computing is maturing, and the security threat associated with quantum computing will be faced in the transmissions of IoT devices, which mainly use wireless communication technologies. Therefore, to ensure the protection of transmitted data, a cryptographic algorithm that is efficient in defeating quantum computer attacks needs to be developed. In this paper, we propose a device authentication and secure communication system with post-quantum cryptography (PQC) for AIoT environments using the NTRU and Falcon signature mechanism, which can resist quantum computer attacks and be used in AIoT environments to effectively protect the confidentiality, integrity, and non-repudiation of transmitted data. We also used Raspberry Pi to simulate AIoT devices for implementation. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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13 pages, 2519 KiB  
Article
Synchronizing TSN Devices via 802.1AS over 5G Networks
by Anas Bin Muslim, Ralf Tönjes and Thomas Bauschert
Electronics 2024, 13(4), 768; https://doi.org/10.3390/electronics13040768 - 15 Feb 2024
Viewed by 642
Abstract
The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option [...] Read more.
The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option to synchronize either of the networks to the other. The TSN time synchronization over 5G is possible either by using the IEEE 1588 generalized Precision Time Protocol (gPTP) based on UDP/IP multicast or via IEEE 802.1AS based on Ethernet PDUs. The INET and Simu5G simulation frameworks, which are both based on the OMNeT++ discrete event simulator, are widely used for simulating TSN and 5G networks. The INET framework comprises the 802.1AS based time synchronization mechanism, and Simu5G provides the 5G user plane carrying IP PDUs. We modified the 802.1AS-based synchronization model of INET so that it works over UDP/IP. With that, it is possible to synchronize TSN slaves (connected to 5G UEs), across a 5G network, with a TSN master clock, present within a TSN network, that is connected to the 5G core network. Our simulation results show that 500 microseconds of synchronization accuracy can be achieved with the corrected asymmetric propagation delay of uplink and downlink between the gNodeB (gNB) and the User Equipment (UE). Furthermore, the synchronization accuracy can be improved if the delay difference between uplink and downlink is known. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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17 pages, 2615 KiB  
Article
A Low-Latency Approach for RFF Identification in Open-Set Scenarios
by Bo Zhang, Tao Zhang, Yuanyuan Ma, Zesheng Xi, Chuan He, Yunfan Wang and Zhuo Lv
Electronics 2024, 13(2), 384; https://doi.org/10.3390/electronics13020384 - 17 Jan 2024
Viewed by 604
Abstract
Radio frequency fingerprint (RFF) identification represents a promising technique for lightweight device authentication. However, current research on RFF primarily focuses on the close-set recognition assumption. Moreover, the high computational complexity and excessive latency during the identification stage represent an intolerable burden for Internet [...] Read more.
Radio frequency fingerprint (RFF) identification represents a promising technique for lightweight device authentication. However, current research on RFF primarily focuses on the close-set recognition assumption. Moreover, the high computational complexity and excessive latency during the identification stage represent an intolerable burden for Internet of Things (IoT) devices. In this paper, we propose a deep-learning-based RFF identification framework in relation to open-set scenarios. Specifically, we leverage a simulated training scheme, in which we strategically designate certain devices as simulated unknowns. This allows us to fine-tune our extractor to better handle open-set recognition. Additionally, we construct an exemplar set that only contains representative RFF features to further reduce time consumption in the identification stage. The experiments are carried out on a hardware platform involving LoRa devices and using a USRP N210 software-defined radio receiver. The results show that the proposed framework can achieve 90.23% accuracy for rogue device detection and 93.85% accuracy for legitimate device classification. Furthermore, it is observed that using an exemplar set consisting of half the total data size can reduce the time overhead by 58% compared to using the entire dataset. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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25 pages, 1335 KiB  
Article
An Efficient Transmitter Feature Extraction Scheme with IQ Imbalance and Nonlinearity in TDD OFDM Systems
by Yi Huang, Aiqun Hu, Jiayi Fan, Huifeng Tian, Xuebao Li and Yanfang Zheng
Electronics 2023, 12(19), 4108; https://doi.org/10.3390/electronics12194108 - 30 Sep 2023
Viewed by 582
Abstract
Radio frequency (RF) fingerprints have been an emerging research topic for the last decade. Numerous algorithms for recognition have been proposed. However, very few algorithms for the accurate extraction of IQI and PA nonlinearity are available, especially when multiple paths are considered. In [...] Read more.
Radio frequency (RF) fingerprints have been an emerging research topic for the last decade. Numerous algorithms for recognition have been proposed. However, very few algorithms for the accurate extraction of IQI and PA nonlinearity are available, especially when multiple paths are considered. In this study, we present a scheme that uses the transmitter in-phase/quadrature-phase imbalance (IQI) and the power amplifier (PA) nonlinearity as RF fingerprint features in time-division duplexing (TDD) OFDM systems, which are always considered to be harmful to data transmission. The scheme consists of two round trips with four steps for two cases: in the first, the IQI and PA nonlinearity are unknown at the terminal; in the second, they are known at the terminal. A channel state information (CSI)-tracking algorithm based on the sliding-window least squares method is first adopted at the terminal. In case A, the obtained CSI is sent to the base station (BS) to remove its impact there; in case B, this removal is conducted directly by using pre-equalization at the terminal. Then, by following a sequential iterative approach, the IQI and nonlinearity are individually calculated. Theoretical analyses reveal how CSI estimation errors influence subsequent estimates at the BS in these two cases. Furthermore, the approximate unbiasedness is verified. The theoretical variance and Cramer–Rao lower bound (CRLB) are also given. It is indicated that the theoretical minimum variance in case B is lower than that in case A from the perspective of the CRLB. The numerical results demonstrate the efficiency of the scheme in comparison with existing techniques in the literature. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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15 pages, 1235 KiB  
Article
Research on Illegal Mobile Device Identification Based on Radio Frequency Fingerprint Feature
by Zhipeng Shao, Zhuo Lv, Wengting Wang and Tao Zhang
Electronics 2023, 12(14), 3144; https://doi.org/10.3390/electronics12143144 - 20 Jul 2023
Cited by 1 | Viewed by 1064
Abstract
Internet of Things (IoT) technology is widely used in new power systems, and it also provides many new modes for network attacks. Illegal terminal device identification is also a significant topic in the field of wireless authentication technology. Some kinds of power network [...] Read more.
Internet of Things (IoT) technology is widely used in new power systems, and it also provides many new modes for network attacks. Illegal terminal device identification is also a significant topic in the field of wireless authentication technology. Some kinds of power network equipment are located in sparsely populated areas and rely on IoT terminals for real-time monitoring. Attackers use illegal terminals to connect power IoT devices for production monitoring and to carry out network attacks, which may cause serious damage, such as power data theft and misoperation of power network equipment. Radio frequency fingerprint (RFF) can extract hardware features from different devices, and is widely used for device identification and authentication. The area over which power network equipment placed is vast, and there are many wireless communication devices and terminals. It is difficult to identify illegal devices through commonly used network management techniques, thus making it difficult to distinguish between the mobile terminals of employees and illegal terminals in general spectrum screening. In response to the above situation, this paper uses the characteristics of the squared spectrum of random access preamble signals to extract hardware device features, proposes an illegal device identification algorithm based on Gaussian distribution theory, and evaluates its performance. The experimental results show that, when the signal-to-noise ratio (SNR) is greater than 15 dB, the average recognition result is greater than 92%. In addition, the algorithm has low computational complexity and high engineering application value. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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Review

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35 pages, 2811 KiB  
Review
A Thorough Review and Comparison of Commercial and Open-Source IoT Platforms for Smart City Applications
by Nikolaos Monios, Nikolaos Peladarinos, Vasileios Cheimaras, Panagiotis Papageorgas and Dimitrios D. Piromalis
Electronics 2024, 13(8), 1465; https://doi.org/10.3390/electronics13081465 - 12 Apr 2024
Viewed by 482
Abstract
In this paper, we conducted a state-of-the-art survey on the current state of IoT platforms suitable for the development of smart city (SC) applications. Both commercial and open-source IoT platforms are presented and compared, addressing various significant aspects and characteristics of SC applications, [...] Read more.
In this paper, we conducted a state-of-the-art survey on the current state of IoT platforms suitable for the development of smart city (SC) applications. Both commercial and open-source IoT platforms are presented and compared, addressing various significant aspects and characteristics of SC applications, such as connectivity, communication protocols, dashboards/analytics availability, security, etc. The characteristics of all the investigated platforms were aggregated so that useful outcomes regarding the technological trends of the IoT platforms could be derived. Furthermore, an attempt was made to identify any discrepancies between the needs of smart cities and the capabilities provided by the relevant platforms. Moreover, IoT platforms referring to the domains of industry, agriculture, and asset tracking were also included, alongside platforms that purely target smart cities, as parts of them are also applicable to smart city applications. The results of the comparison proved that there is a lack of open-source IoT platforms targeted at smart cities, which impedes the development and testing of connected smart city applications for researchers. Full article
(This article belongs to the Special Issue Precise Timing and Security in Internet of Things)
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