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Hardware-Based Security Techniques for Smart/Intelligent Sensor Systems

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

Deadline for manuscript submissions: 31 October 2026 | Viewed by 553

Special Issue Editors


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Guest Editor
Department of Computer Science, Sam Houston State University, Huntsville, TX 77340, USA
Interests: IoT; sensor network; hardware security; vehicular network security
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computer science, College of Charleston, Charleston, SC, USA
Interests: security; blockchain; smart grids; FL; adversarial machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technological advancements in sensor technologies are rapidly transforming the internet landscape. Intelligent sensing devices, including the Internet of Things (IoT), have introduced a dynamic new ecosystem that is now integral to a wide range of data communication networks, including manufacturing, industrial control systems, healthcare, transportation, and military applications.

However, the widespread adoption of sensor devices has also significantly increased the attack surface for cyber threats. These threats include authentication bypass, device identification attacks, sensor cloning, side-channel attacks, hardware tampering, exploitation of sensor I/O interfaces, denial-of-service (DoS), and sensor data injection attacks. This challenge is further exacerbated by the limited computational and energy resources typical of sensor devices, which render traditional software-based security solutions often infeasible.

This Special Issue invites the submission of high-quality, original, and unpublished research articles that focus on software and hardware sensor vulnerability assessments, including novel hardware-based security techniques, trustworthy architectures, and security isolation methodologies based on ARM trust zone technology designed to protect these systems. Submissions may target a variety of platforms, including autonomous mobile systems, ARM processor cores, drone flight control systems, reconfigurable systems (e.g., FPGA-based), biomedical sensing systems, cyber–physical systems (CPSs), crypto modules, RFID, IoT devices, and embedded sensor modules. Both theoretical studies and experimental works involving system design and implementation are highly encouraged to be submitted to this Special Issue.

Topics of interest include, but are not limited to, the following:

  • Hardware-based defensive strategies against side-channel attacks on sensing units.
  • Lightweight hardware mechanisms to counter data spoofing attacks in drone systems.
  • Vulnerability assessment of UAV sensor data.
  • Energy-efficient data encryption techniques tailored for IoT devices and sensors.
  • Intrusion detection systems leveraging physical characteristics of sensing units.
  • Hardware-level device identification techniques to mitigate sensor device cloning.
  • Security assessment of hardware vulnerabilities in mobile platforms and autonomous aerial systems.
  • Machine learning and federated learning techniques tailored for IoT devices and sensors.

Dr. Amar Rasheed
Dr. Mohamed Baza
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

  • hardware-based security
  • Internet of Things (IoT)
  • intelligent sensing
  • sensor device

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Published Papers (1 paper)

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Research

28 pages, 7531 KB  
Article
A UAV Testbed for Diagnosing Hardware Vulnerabilities: Quantifying Sim-to-Real Discrepancies in PX4 Flight Logs
by Kubra Kose, Jacob Wing, Nuri Alperen Kose, Carlos Guadarrama-Trejo, Ayden Sowers and Amar Rasheed
Sensors 2026, 26(10), 3188; https://doi.org/10.3390/s26103188 - 18 May 2026
Viewed by 213
Abstract
This paper presents a comprehensive UAV testbed that establishes quantitative baselines for hardware vulnerability diagnosis and cyber–physical security validation by leveraging comparative flight logs from PX4-based Software-In-The-Loop (SITL) simulations and multiple real-world quadrotor missions. The testbed utilizes a unified data pipeline centered on [...] Read more.
This paper presents a comprehensive UAV testbed that establishes quantitative baselines for hardware vulnerability diagnosis and cyber–physical security validation by leveraging comparative flight logs from PX4-based Software-In-The-Loop (SITL) simulations and multiple real-world quadrotor missions. The testbed utilizes a unified data pipeline centered on the uORB message bus and ULog format, enabling the extraction of high-resolution telemetry, including raw Inertial Measurement Unit (IMU) data, state-estimation, and actuator control signals. Evaluated across varying environmental conditions, side-by-side time-series and statistical analyses reveal critical sim-to-real discrepancies in sensor fidelity, GPS interference, and onboard resource behavior that are often overlooked in virtual environments. Real-world data exposes hardware-induced noise, mechanical vibrations, and electromagnetic disturbances that significantly impact flight stability and system reliability. By mathematically quantifying these discrepancies (e.g., via variance and probability distribution shifts), the proposed testbed establishes a rigorous baseline for distinguishing natural physical variability from anomalous or adversarial behavior. Ultimately, this work provides a foundational framework for developing robust anomaly detection models and validating the cyber–physical security of autonomous UAV systems in safety-critical environments. Full article
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