LoRaWAN Security: An Evolvable Survey on Vulnerabilities, Attacks and their Systematic Mitigation

Hessel, Frank; Almon, Lars; Hollick, Matthias

doi:10.1145/3561973

Cited by 5 publications

(2 citation statements)

References 81 publications

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“…[79,80] LoRa simulators Presented a comparative study simulation tool for the simulation of LoRa/LoRaWAN networks. [81] LoRaWAN security Highlighted vulnerabilities and security attacks, discussed their systematic mitigation approaches. [82] Recent advancement in LoRa Reviewed LoRa concerning analysis, communication, security, and applications.…”

Section: Refmentioning

confidence: 99%

LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning

Farhad

Pyun

2023

Sensors

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The Internet of Things is rapidly growing with the demand for low-power, long-range wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one such technology that has gained significant attention in recent years due to its ability to provide long-range communication with low power consumption. One of the main issues in LoRaWAN is the efficient utilization of radio resources (e.g., spreading factor and transmission power) by the end devices. To solve the resource allocation issue, machine learning (ML) methods have been used to improve the LoRaWAN network performance. The primary aim of this survey paper is to study and examine the issue of resource management in LoRaWAN that has been resolved through state-of-the-art ML methods. Further, this survey presents the publicly available LoRaWAN frameworks that could be utilized for dataset collection, discusses the required features for efficient resource management with suggested ML methods, and highlights the existing publicly available datasets. The survey also explores and evaluates the Network Simulator-3-based ML frameworks that can be leveraged for efficient resource management. Finally, future recommendations regarding the applicability of the ML applications for resource management in LoRaWAN are illustrated, providing a comprehensive guide for researchers and practitioners interested in applying ML to improve the performance of the LoRaWAN network.

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Section: Refmentioning

confidence: 99%

LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning

Farhad

Pyun

2023

Sensors

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“…It is also important to bear in mind that, for example, in an urban or industrial environment, LoRaWAN deployments will continue to operate for up to many decades, while continuously maintaining operational security and upgrading security standards. Even surveys have been developed in the area of evaluating LoRaWAN security changes over time [47].…”

mentioning

confidence: 99%

Analysis of Cyber Security Aspects of Data Transmission in Large-Scale Networks Based on the LoRaWAN Protocol Intended for Monitoring Critical Infrastructure Sensors

Czeczot,

Rojek,

Mikołajewski

2023

Electronics

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Cyber security is nowadays synonymous with the reliability of elements connected to the internet. Better control of factories, security systems or even individual sensors is possible through the use of Internet of Things technology. The security of the aforementioned structures and the data they transmit has been a major concern in the development of IoT solutions for wireless data transmission. If we add to this prospect of low-cost end devices, we can seriously consider implementing such solutions in critical infrastructure areas. This article aims to assess the state of the art and experience and identify the main risks and directions for further development in order to improve the cyber security situation of LoRaWAN-based networks. LoRaWAN meets the three key requirements of IoT applications (low cost, large-scale deployability, high energy efficiency) through an open standard and the construction of autonomous networks without third-party infrastructure. However, many research issues remain to be solved/improved such as resource allocation, link coordination, transmission reliability, performance and, above all, security. Thus, we have defined a research gap in the area of LoRaWAN security. The contribution of this work is to structure the knowledge in the field of LoRaWAN security, based on previous publications and our own experience, in order to identify challenges and their potential solutions. This will help move LoRaWAN security research to the next stage.

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