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Biometric and Cryptographic Techniques and Their Applications in Sensor Data and Network Security

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

Deadline for manuscript submissions: 25 August 2026 | Viewed by 2333

Special Issue Editors

Dr. Wencheng Yang

E-Mail Website
Guest Editor
School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, QLD 4350, Australia
Interests: biometrics; AI security and privacy
Special Issues, Collections and Topics in MDPI journals
Dr. Fei Zhu

E-Mail Website
Guest Editor
School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan 430200, China
Interests: data security; privacy-preserving; AI security

Special Issue Information

Dear Colleagues,

Biometric and cryptographic technologies have become integral to modern sensor-based systems and network infrastructures, enabling stronger security, privacy, and trust in an increasingly interconnected world. As sensors proliferate in domains such as healthcare, IoT, smart grids, and critical infrastructures, the secure collection, transmission, and storage of sensitive data become vital. Biometric authentication methods, leveraging unique physiological and behavioral traits, offer robust identity verification, while cryptographic techniques provide the mathematical foundation for confidentiality, integrity, and resilience against cyber threats.

This Special Issue aims to bring together cutting-edge research and practical advances at the intersection of biometrics, cryptography, and sensor-driven networks. We invite contributions that address emerging challenges in protecting sensor data and network communications, with a focus on novel algorithms, architectures, and applications that enhance security and privacy. Topics of interest include secure biometric template design, lightweight cryptographic protocols for resource-constrained devices, privacy-preserving authentication frameworks, and real-world deployments in networked sensor environments. Through this collection, we aim to foster interdisciplinary dialogue and provide insights that support the development of secure, reliable, and trustworthy sensor systems.

Dr. Wencheng Yang
Dr. Fei Zhu
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

  • biometric authentication
  • cryptographic protocols
  • privacy-preserving techniques
  • sensor data security
  • network security
  • lightweight cryptography
  • secure template protection
  • Internet of Things (IoT)
  • privacy and trust in sensor networks
 

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Published Papers (3 papers)

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31 pages, 2844 KB  
Article
A Security-Enhanced Certificateless Aggregate Authentication Protocol with Revocation for Wireless Medical Sensor Networks
by Quan Fan, Yimin Wang and Xiang Li
Sensors 2026, 26(7), 2106; https://doi.org/10.3390/s26072106 - 28 Mar 2026
Viewed by 331
Abstract
Wireless medical sensor networks (WMSNs) enable continuous patient monitoring by transmitting sensitive physiological data over open wireless links. Given the resource-constrained nature and large-scale deployment of such networks, authentication mechanisms must be both lightweight and privacy-preserving. Moreover, due to the frequent turnover of [...] Read more.
Wireless medical sensor networks (WMSNs) enable continuous patient monitoring by transmitting sensitive physiological data over open wireless links. Given the resource-constrained nature and large-scale deployment of such networks, authentication mechanisms must be both lightweight and privacy-preserving. Moreover, due to the frequent turnover of patients and devices in hospital environments, timely member revocation is crucial to prevent discharged or compromised entities from injecting forged reports that could mislead medical diagnosis. Although existing pairing-free certificateless aggregate authentication schemes are efficient, they often suffer from critical security and privacy vulnerabilities. Recently, an efficient certificateless authentication scheme with revocation has been proposed. However, our analysis reveals that the scheme presents the following security vulnerabilities: (i) member witnesses can be recovered from public information, (ii) revocation checks can be bypassed via identity grafting attack, and (iii) user identities can be linked due to the long-term use of static pseudonyms. To address these issues, we propose a security-enhanced certificateless aggregate authentication protocol with revocation for WMSNs. Our design enforces strong identity–membership binding to resist grafting attacks, employs a non-interactive zero-knowledge membership proof to preserve witness secrecy, and adopts dynamic pseudonym rotation to achieve unlinkability. We provide formal security proofs and comprehensive performance comparisons. The results indicate that, at the same security level, our protocol achieves more efficient signature verification while maintaining communication overhead comparable to existing schemes. In addition, the overhead introduced by our revocation mechanism remains constant, making it well suited for large-scale WMSNs deployments with frequent membership changes. Full article
(This article belongs to the Special Issue Biometric and Cryptographic Techniques and Their Applications in Sensor Data and Network Security)
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13 pages, 607 KB  
Article
A Secure and Efficient Authentication Scheme with Privacy Protection for Internet of Medical Things
by Feihong Xu, Jianbo Wu, Qing An and Rahman Ziaur
Sensors 2026, 26(1), 313; https://doi.org/10.3390/s26010313 - 3 Jan 2026
Viewed by 754
Abstract
The Internet of Medical Things represents a pivotal application of Internet of Things technology in Healthcare 4.0, offering substantial practical benefits in enhancing medical quality, reducing costs, and minimizing errors. In history, researchers have proposed numerous privacy-preserving authentication schemes to safeguard Internet of [...] Read more.
The Internet of Medical Things represents a pivotal application of Internet of Things technology in Healthcare 4.0, offering substantial practical benefits in enhancing medical quality, reducing costs, and minimizing errors. In history, researchers have proposed numerous privacy-preserving authentication schemes to safeguard Internet of Medical Things applications. Nevertheless, due to design shortcomings, existing solutions still encounter significant security and performance challenges, rendering them impractical for real-world use. To resolve the issue, this work introduces a novel practical Internet of Medical Things-based smart healthcare system, leveraging a pairing-free certificateless signature scheme and hash-based message authentication code. Through formal security proofs under standard cryptographic assumptions, and performance analysis, our scheme demonstrates enhanced security while maintaining desirable computational and communication efficiency. Full article
(This article belongs to the Special Issue Biometric and Cryptographic Techniques and Their Applications in Sensor Data and Network Security)
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21 pages, 358 KB  
Article
What the Heart Can(not) Tell: Potential and Pitfalls of Biometric Recognition Methods Based on Photoplethysmography
by Lidia Alecci, Matías Laporte, Leonardo Alchieri, Nouran Abdalazim and Silvia Santini
Sensors 2025, 25(24), 7586; https://doi.org/10.3390/s25247586 - 14 Dec 2025
Viewed by 731
Abstract
Human physiological signals collected through wearable devices enable a range of applications, including biometric authentication. Prior studies have demonstrated the potential of using physiological signals to uniquely identify individuals, but their validity in real-world scenarios remains limited. Most existing work relies on controlled [...] Read more.
Human physiological signals collected through wearable devices enable a range of applications, including biometric authentication. Prior studies have demonstrated the potential of using physiological signals to uniquely identify individuals, but their validity in real-world scenarios remains limited. Most existing work relies on controlled experimental settings, small datasets, short-term evaluations, and the absence of unseen-user testing—factors that tend to produce overly optimistic performance estimates. Although recent research highlights the need for broader benchmarking and reproducible protocols, systematic evaluations remain scarce. In this study, we assess the reliability of photoplethysmography (PPG)-based biometric methods. We replicate two published approaches and introduce a feature-based method as a baseline, evaluating all three under multiple conditions. Our results show that while these methods perform well in laboratory datasets, their effectiveness declines substantially in real-world environments, where signal variability, larger user populations, and temporal separation between training and testing challenge current systems. To address these issues, we propose guidelines for the robust evaluation of PPG-based biometrics, emphasizing real-world and longitudinal datasets, temporal splits, unseen-user assessments, and transparent reporting. Although developed for PPG, these recommendations generalize to other physiological biometrics and aim to improve the reliability and reproducibility of future research. Full article
(This article belongs to the Special Issue Biometric and Cryptographic Techniques and Their Applications in Sensor Data and Network Security)
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