LPWAN Cyber Security Risk Analysis: Building a Secure IQRF Solution

Bouzidi, Mohammed; Amro, Ahmed; Dalveren, Yaser; Cheikh, Faouzi Alaya

doi:10.3390/s23042078

Cited by 3 publications

(2 citation statements)

References 42 publications

(50 reference statements)

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“…The wireless sensor network of IoT exhibits vulnerabilities across various layers, and cyberattacks can manifest at different stages [66]. Likewise, LPWAN is not exempt from cyber threats [67]. Wireless sensor networks in smart grids comprise IoT devices equipped with temperature, humidity, light, and wind sensors.…”

Section: Security Considerationsmentioning

confidence: 99%

Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids

Awan,

Dalveren,

Catak

et al. 2023

Electronics

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Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart grids, cybersecurity of IoT is paramount. To this end, use of cryptographic security methods is prevalent in existing IoT. Non-cryptographic methods such as radio frequency fingerprinting (RFF) have been on the horizon for a few decades but are limited to academic research or military interest. RFF is a physical layer security feature that leverages hardware impairments in radios of IoT devices for classification and rogue device detection. The article discusses the potential of RFF in wireless communication of IoT devices to augment the cybersecurity of smart grids. The characteristics of a deep learning (DL)-aided RFF system are presented. Subsequently, a deployment framework of RFF for smart grids is presented with implementation and regulatory aspects. The article culminates with a discussion of existing challenges and potential research directions for maturation of RFF.

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Section: Security Considerationsmentioning

confidence: 99%

Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids

Awan,

Dalveren,

Catak

et al. 2023

Electronics

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“…Since industrial control protocol information can directly or indirectly transmit the operation status or operation of industrial software, there are potential safety risks. The development of informatization has led to the interconnection of IT/OT networks, simplifying the digital operation process, and inevitably creating vulnerabilities that are vulnerable to attacks, posing more threats to the system [5]. Attacks against industrial control protocols and traditional industrial software security vulnerabilities have made industrial production and manufacturing the target of numerous attackers.…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Using Seq-GAN Model in Vulnerability Detection of Industrial Control Protocols

Zhang,

Zou,

Zeng

et al. 2024

JCSANDM

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Continuous improvement of internet technology has driven the continuous progress and improvement of industrial control systems, and provided more support for security vulnerability detection in this field. Combining the GAN model, the detection model based on Seq-GAN in industrial control protocol vulnerabilities constructed in this article provides more options for further improving the security of industrial control systems, and can detect and analyse security vulnerabilities in industrial control protocols more efficiently and accurately. By comparing the performance of different models for security vulnerability detection, the Seq-GAN model has smaller prediction errors, can also obtain higher G-mean and F1-score values, and has sufficient reliability. At the same time, it can also improve the efficiency of vulnerability detection in industrial control systems, and can achieve better comprehensive detection performance. Therefore, the application of the Seq-GAN model in industrial control protocol vulnerability detection can provide more support for improving security detection in this field.

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Stability Analysis through a Stability Factor Metric for IQRF Mesh Sensor Networks Utilizing Merged Data Collection

Sebestyen,

Kopjak

2024

Sensors

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This paper introduces a novel stability metric specifically developed for IQRF wireless mesh sensor networks, emphasizing flooding routing and data collection methodologies, particularly IQRF’s Fast Response Command (FRC) technique. A key feature of this metric is its ability to ensure network resilience against disruptions by effectively utilizing redundant paths in the network. This makes the metric an indispensable tool for field engineers in both the design and deployment of wireless sensor networks. Our findings provide valuable insights, demonstrating the metric’s efficacy in achieving robust and reliable network operations, especially in data collection tasks. The inclusion of redundant paths as a factor in the stability metric significantly enhances its practicality and relevance. Furthermore, this research offers practical ideas for enhancing the design and management of wireless mesh sensor networks. The stability metric uniquely assesses the resilience of data collection activities within these networks, with a focus on the benefits of redundant paths, underscoring the significance of stability in network evaluation.

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LPWAN Cyber Security Risk Analysis: Building a Secure IQRF Solution

Cited by 3 publications

References 42 publications

Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids

Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids

Feasibility of Using Seq-GAN Model in Vulnerability Detection of Industrial Control Protocols

Stability Analysis through a Stability Factor Metric for IQRF Mesh Sensor Networks Utilizing Merged Data Collection

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