Smart City Gnosys
Smart city article details
| Title | Deployment And Implementation Aspects Of Radio Frequency Fingerprinting In Cybersecurity Of Smart Grids |
|---|---|
| ID_Doc | 18363 |
| Authors | Awan M.A.; Dalveren Y.; Catak F.O.; Kara A. |
| Year | 2023 |
| Published | Electronics (Switzerland), 12, 24 |
| DOI | http://dx.doi.org/10.3390/electronics12244914 |
| Abstract | 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. © 2023 by the authors. |
| Author Keywords | cybersecurity; deep learning; Internet of Things; machine learning; radio frequency fingerprinting; smart city; smart grid; software-defined radio |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
38027  | 0.887 | Lu Q.; Yang Z.; Zhang H.; Chen F.; Xian H. | Mrfe: A Deep-Learning-Based Multidimensional Radio Frequency Fingerprinting Enhancement Approach For Iot Device Identification | IEEE Internet of Things Journal, 11, 18 (2024) |
| 44072 | 0.882 | Abbas S.; Abu Talib M.; Nasir Q.; Idhis S.; Alaboudi M.; Mohamed A. | Radio Frequency Fingerprinting Techniques For Device Identification: A Survey | International Journal of Information Security, 23, 2 (2024) |
| 5249 | 0.871 | Chowdhury R.R.; Abas P.E. | A Survey On Device Fingerprinting Approach For Resource-Constraint Iot Devices: Comparative Study And Research Challenges | Internet of Things (Netherlands), 20 (2022) |
| 52813 | 0.85 | Kohli V.; Aman M.N.; Sikdar B. | Sram And Generative Network-Based Physical Fingerprinting For Trust Management In The Internet Of Things | Proceedings - 2023 IEEE Conference on Dependable and Secure Computing, DSC 2023 (2023) |