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Cryptography in Internet of Things
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Cryptography in Internet of Things

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 February 2026) | Viewed by 4528

Special Issue Editors

Dr. Yudi Zhang

E-Mail Website
Guest Editor
Faculty of Engineering and Information Sciences, School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: cryptography; Information Security; cryptographic protocols
Special Issues, Collections and Topics in MDPI journals
Dr. Nan Li

E-Mail Website
Guest Editor
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: cybersecurity; IoT security and privacy; applied cryptography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid proliferation of the Internet of Things (IoT) has revolutionized the way that we interact with technology, seamlessly integrating physical devices into our digital ecosystem. From smart homes and wearable devices to industrial systems and healthcare applications, the IoT is driving unprecedented connectivity and innovation; however, this interconnected world also introduces critical challenges, particularly in securing data and ensuring privacy. Cryptography plays a pivotal role in addressing these challenges by providing the foundation for secure communication, authentication, privacy protection, and data integrity.

This Special Issue explores the cutting-edge advancements in cryptographic techniques tailored for IoT environments. Traditional cryptographic methods often struggle to meet the unique constraints of IoT devices, such as limited computational power, energy efficiency, and network scalability. This Special Issue highlights novel approaches and lightweight cryptographic solutions that address these limitations while maintaining robust security standards. We seek original and high-quality research papers that are related, but not limited, to topics including secure key management, end-to-end encryption, post-quantum cryptography for the IoT, lightweight authentication protocols, and blockchain-based solutions for decentralized security.

Dr. Yudi Zhang
Dr. Nan Li
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. 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

  • applied cryptography
  • security protocols
  • IoT security
  • cloud security
  • blockchain technology

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Published Papers (4 papers)

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Research

17 pages, 2678 KB  
Article
A Cyber Attack Path Prediction Approach Based on a Text-Enhanced Graph Attention Mechanism
by Hanjun Gao, Hang Tong, Baoyan Yong and Gang Shen
Electronics 2026, 15(3), 552; https://doi.org/10.3390/electronics15030552 - 27 Jan 2026
Viewed by 576
Abstract
In order to solve the problem of traditional methods not being able to discover hidden attack trajectories, we propose a cyber attack path prediction approach based on a text-enhanced graph attention mechanism in this paper. Specifically, we design an ontology that captures multi-dimensional [...] Read more.
In order to solve the problem of traditional methods not being able to discover hidden attack trajectories, we propose a cyber attack path prediction approach based on a text-enhanced graph attention mechanism in this paper. Specifically, we design an ontology that captures multi-dimensional links between vulnerabilities, weaknesses, attack patterns, and tactics by integrating CVE, CWE, CAPEC, and ATT&CK into Neo4j. Then, we inject natural language descriptions into the attention mechanism to develop a text-enhanced GAT that can alleviate data sparsity. The experiment shows that compared with existing baselines, our approach improveds MRR and Hits@5 by 12.3% and 13.2%, respectively. Therefore, the proposed approach can accurately predict attack paths and support active cyber defense. Full article
(This article belongs to the Special Issue Cryptography in Internet of Things)
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19 pages, 1176 KB  
Article
An Efficient Certificate-Based Linearly Homomorphic Signature Scheme for Secure Network Coding
by Yumei Li, Yudi Zhang, Willy Susilo and Fuchun Guo
Electronics 2026, 15(3), 503; https://doi.org/10.3390/electronics15030503 - 23 Jan 2026
Viewed by 299
Abstract
With the development of mobile crowdsensing systems (MCSs), wireless network transmission efficiency has attracted widespread attention. Network coding can be used in wireless communication to improve network throughput and robustness, which allows intermediate nodes to perform arbitrary coding operations on data packets. However, [...] Read more.
With the development of mobile crowdsensing systems (MCSs), wireless network transmission efficiency has attracted widespread attention. Network coding can be used in wireless communication to improve network throughput and robustness, which allows intermediate nodes to perform arbitrary coding operations on data packets. However, the data packet in network coding systems is vulnerable to pollution attacks. The special operation of intermediate nodes makes some security protocols in traditional store-and-forward networks unavailable in network coding systems. To address this problem, an efficient certificate-based linearly homomorphic signature scheme against pollution attacks in network coding systems is presented. A novel homomorphic contraction mapping technique is introduced to reduce the computational cost of signature generation. In the proposed scheme, the computational cost of both signature generation and verification is independent of the data packet size. Furthermore, a construction is provided to simultaneously defend against both eavesdropping attacks and pollution attacks in unicast networks. The security of the certificate-based linearly homomorphic signature scheme is formally proved in the random oracle model (ROM), and the scheme is implemented using the Java Pairing-Based Cryptography (JPBC) library. Simulation results demonstrate that the scheme is efficient and practical for real-world deployments in public environments without requiring secure channels. Full article
(This article belongs to the Special Issue Cryptography in Internet of Things)
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25 pages, 823 KB  
Article
Optimizing SPHINCS+ for Low-Power Devices
by Alexander Magyari and Yuhua Chen
Electronics 2025, 14(17), 3460; https://doi.org/10.3390/electronics14173460 - 29 Aug 2025
Cited by 3 | Viewed by 1872
Abstract
Different optimization techniques for the SHAKE variant of SPHINCS+ are explored on an FPGA with the means to find a power-efficient model for resource-constrained devices. This work explores multiple hashing implementations, such as registering inputs and directly feeding data to hashing units, as [...] Read more.
Different optimization techniques for the SHAKE variant of SPHINCS+ are explored on an FPGA with the means to find a power-efficient model for resource-constrained devices. This work explores multiple hashing implementations, such as registering inputs and directly feeding data to hashing units, as well as different variations in hashing permutations per clock cycle. The design is evaluated based on resource requirements, the signature generation rate, and both static and active power consumption. This design shows a decrease in energy consumed per signature by 20% to 30% compared to other state-of-the-art SPHINCS+ implementations, while only using 12–14k lookup tables (LUTs), depending on the SPHINCS+ variant. Moreover, an amendment is proposed to the SPHINCS+ specification that allows for decreased processing time and memory consumption while maintaining the security level and non-deterministic properties. This is accomplished by rearranging the inputs in the random oracle model. Full article
(This article belongs to the Special Issue Cryptography in Internet of Things)
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12 pages, 759 KB  
Article
Privacy-Preserving Byzantine-Tolerant Federated Learning Scheme in Vehicular Networks
by Shaohua Liu, Jiahui Hou and Gang Shen
Electronics 2025, 14(15), 3005; https://doi.org/10.3390/electronics14153005 - 28 Jul 2025
Viewed by 1108
Abstract
With the rapid development of vehicular network technology, data sharing and collaborative training among vehicles have become key to enhancing the efficiency of intelligent transportation systems. However, the heterogeneity of data and potential Byzantine attacks cause the model to update in different directions [...] Read more.
With the rapid development of vehicular network technology, data sharing and collaborative training among vehicles have become key to enhancing the efficiency of intelligent transportation systems. However, the heterogeneity of data and potential Byzantine attacks cause the model to update in different directions during the iterative process, causing the boundary between benign and malicious gradients to shift continuously. To address these issues, this paper proposes a privacy-preserving Byzantine-tolerant federated learning scheme. Specifically, we design a gradient detection method based on median absolute deviation (MAD), which calculates MAD in each round to set a gradient anomaly detection threshold, thereby achieving precise identification and dynamic filtering of malicious gradients. Additionally, to protect vehicle privacy, we obfuscate uploaded parameters to prevent leakage during transmission. Finally, during the aggregation phase, malicious gradients are eliminated, and only benign gradients are selected to participate in the global model update, which improves the model accuracy. Experimental results on three datasets demonstrate that the proposed scheme effectively mitigates the impact of non-independent and identically distributed (non-IID) heterogeneity and Byzantine behaviors while maintaining low computational cost. Full article
(This article belongs to the Special Issue Cryptography in Internet of Things)
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