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Sensors
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Security, Trust and Privacy in Internet of Things
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Security, Trust and Privacy in Internet of Things

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

Deadline for manuscript submissions: 30 August 2026 | Viewed by 1336

Special Issue Editors

Dr. Alex Akinbi

E-Mail Website
Guest Editor
Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M15 6BX, UK
Interests: mobile; IoT; embedded systems; cloud forensics; security and privacy; computer security and vulnerability research; reverse engineering and exploit development
Dr. Safiullah Khan

E-Mail Website
Guest Editor
Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M15 6BX, UK
Interests: cryptography; Internet of Things; embedded systems; lightweight cryptography (LWC) and post-quantum cryptography (PQC)
Special Issues, Collections and Topics in MDPI journals
Dr. Max Hashem Eiza

E-Mail Website
Guest Editor
Faculty of Engineering and Technology, School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool L3 3AF, UK
Interests: cyber security; privacy; zero trust; 5G/6G networks; IoT; blockchain
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) has revolutionized the way we interact with technology, connecting devices, and systems to create smarter environments. Many of these devices are interconnected and support businesses and key critical national infrastructures. However, this connectivity brings significant challenges in terms of security, trust, and privacy.

This Special Issue considers the latest research and developments addressing these critical challenges, exploring innovative solutions to safeguard IoT ecosystems and ensure security, user trust, and data privacy.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Data Privacy and Security of the Internet of Everything;
  • Zero Trust and Trust Management of Smart Environments;
  • Blockchain and Distributed Ledger Technologies for IoT Security;
  • Post-Quantum Cryptography Solutions for IoT and Embedded Systems;
  • Secure Communication in IoT Ecosystems and Networks;
  • Privacy-Preserving Protocols for IoT Ecosystems;
  • Lightweight Cryptography for IoT Devices;
  • Hardware-Based Security Primitives for IoT.

Dr. Alex Akinbi
Dr. Safiullah Khan
Dr. Max Hashem Eiza
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 250 words) can be sent to the Editorial Office for assessment.

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. Sensors 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 2600 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

  • IoT
  • privacy
  • security
  • blockchain
  • cryptography

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Published Papers (2 papers)

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Research

18 pages, 330 KB  
Article
A Lightweight Hybrid Authentication and Key Agreement Protocol for Decentralized Device-to-Device Communication with Post-Quantum Confidentiality
by Asday Savón-Berenguer, Sorin-Aurel Moraru, Juan Carlos García-Naranjo and An Braeken
Sensors 2026, 26(10), 3040; https://doi.org/10.3390/s26103040 - 12 May 2026
Viewed by 277
Abstract
Device-to-device (D2D) communication is expected to become a key component of 6G and IoT systems, enabling low-latency and infrastructure-independent connectivity. A major challenge is to establish secure session keys between previously unknown devices without relying on an online trusted third party, while also [...] Read more.
Device-to-device (D2D) communication is expected to become a key component of 6G and IoT systems, enabling low-latency and infrastructure-independent connectivity. A major challenge is to establish secure session keys between previously unknown devices without relying on an online trusted third party, while also ensuring resilience against future quantum adversaries. This paper proposes a lightweight hybrid authentication and key agreement protocol for decentralized D2D communication. The approach combines IPFS-assisted distributed key discovery with a two-message protocol that uses post-quantum key encapsulation for long-term confidentiality, while retaining elliptic curve cryptography (ECC) for efficient real-time authentication under classical security assumptions.This design reflects the different temporal security requirements of confidentiality and authentication and provides a practical trade-off between quantum resilience and computational efficiency. The proposed scheme achieves mutual authentication under classical ECC assumptions, secure session key establishment, and resistance against common attacks, while providing post-quantum confidentiality protection against future quantum adversaries and removing the need for an online trusted third party (TTP) during protocol execution. The results demonstrate that the protocol offers a competitive and practical solution for secure decentralized D2D communication in IoT and future 6G environments. Full article
(This article belongs to the Special Issue Security, Trust and Privacy in Internet of Things)
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25 pages, 2809 KB  
Article
E-PTES-S: Enhanced Trust Evaluation via Multidimensional Spatiotemporal Fusion and Variance-Based Stability Sequence Extraction in IoT Sensing Networks
by Jinze Liu, Yongtao Yao, Xiao Liu, Jining Chen, Shaoxuan Li and Jiayi Lin
Sensors 2026, 26(8), 2382; https://doi.org/10.3390/s26082382 - 13 Apr 2026
Viewed by 320
Abstract
Mobile data collectors (MDCs) play a very important role in Internet of Things (IoT) sensing networks. However, ensuring their trustworthiness against insider threats, such as on–off attacks and spatiotemporal fabrication, remains a critical challenge. Existing trust evaluation methods frequently struggle with these threats [...] Read more.
Mobile data collectors (MDCs) play a very important role in Internet of Things (IoT) sensing networks. However, ensuring their trustworthiness against insider threats, such as on–off attacks and spatiotemporal fabrication, remains a critical challenge. Existing trust evaluation methods frequently struggle with these threats due to insufficient evidence dimensions and the inability to quantify behavioral stability. To address these limitations, this paper proposes an enhanced proactive trust evaluation system based on stability sequence extraction (E-PTES-S). E-PTES-S improves the evaluation accuracy by integrating five factors of evidence, stability-computation mechanisms, and an adaptive weight allocation scheme to maintain robustness even when proactive verification data is scarce. In addition to the usual interaction and proactive verification indicators, regional consistency (TRC) and task timeliness (TTT) are introduced to mitigate location falsification and transmit-time deviations more rigorously. Then, a sliding window technique is used to obtain an integrated evidence sequence, which includes a new continuous stability sequence (FCSS) and traditional credible, untrustworthy, and uncertain sequences. This continuous stability sequence adds a variance-based incentive scheme to measure behavioral stability. Finally, the normalized trust value is derived from multiple indicators including multidimensional spatiotemporal evidence and stability metrics. Experimental results show that the proposed E-PTES-S achieves a normal node detection rate of 98.7% under complex dynamic conditions, outperforming the baseline PTES and Trust-SIoT algorithms by approximately 9% and 1%, respectively, while also improving the cumulative data collection profit by 4.8%. Furthermore, robustness analysis demonstrates that E-PTES-S exhibits excellent robustness against physical-layer uncertainties, successfully sustaining an 84.4% detection rate even under severe environmental shadowing. Full article
(This article belongs to the Special Issue Security, Trust and Privacy in Internet of Things)
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