On the detection of unauthorized drones—Techniques and future perspectives: A review

MA Khan, H Menouar, A Eldeeb… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
The market size of civilian drones is tremendously increasing and is expected to reach 1.66
million by the end of 2023. The increase in number of civilian drones poses several privacy …

Machine learning for the detection and identification of Internet of Things devices: A survey

Y Liu, J Wang, J Li, S Niu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a
variety of emerging services and applications. However, the presence of rogue IoT devices …

Radio frequency fingerprint identification for Internet of Things: A survey

L Xie, L Peng, J Zhang, A Hu - Security and Safety, 2024 - sands.edpsciences.org
Radio frequency fingerprint (RFF) identification is a promising technique for identifying
Internet of Things (IoT) devices. This paper presents a comprehensive survey on RFF …

RF fingerprinting unmanned aerial vehicles with non-standard transmitter waveforms

N Soltani, G Reus-Muns, B Salehi, J Dy… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
The universal availability of unmanned aerial vehicles (UAVs) has resulted in many
applications where the same make/model can be deployed by multiple parties. Thus …

Secure industrial iot systems via rf fingerprinting under impaired channels with interference and noise

OM Gul, M Kulhandjian, B Kantarci, A Touazi… - IEEE …, 2023 - ieeexplore.ieee.org
Industrial IoT-enabled critical infrastructures are susceptible to cyber attacks due to their
mission-critical deployment. To ensure security by design, radio frequency (RF)-based …

Analysis of augmentation methods for RF fingerprinting under impaired channels

C Comert, M Kulhandjian, OM Gul, A Touazi… - Proceedings of the …, 2022 - dl.acm.org
Cyber-physical systems such as autonomous vehicle networks are considered to be critical
infrastructures in various applications. However, their mission critical deployment makes …

A real-world dataset generator for specific emitter identification

BP Muller, LJ Wong, WH Clark, AJ Michaels - IEEE Access, 2023 - ieeexplore.ieee.org
Generating high-quality, real-world, well-labeled datasets for radio frequency machine
learning (RFML) applications often proves prohibitively cumbersome and expensive …

The day-after-tomorrow: On the performance of radio fingerprinting over time

A Saeif, S Savio, O Gabriele - Proceedings of the 39th Annual Computer …, 2023 - dl.acm.org
The performance of Radio Frequency (RF) Fingerprinting (RFF) techniques is negatively
impacted when the training data is not temporally close to the testing data. This can limit the …

A deep-learning-based gps signal spoofing detection method for small UAVs

Y Sun, M Yu, L Wang, T Li, M Dong - Drones, 2023 - mdpi.com
The navigation of small unmanned aerial vehicles (UAVs) mainly depends on global
positioning systems (GPSs). However, GPSs are vulnerable to attack by spoofing, which …

Fine-grained augmentation for RF fingerprinting under impaired channels

OM Gul, M Kulhandjian, B Kantarci… - 2022 IEEE 27th …, 2022 - ieeexplore.ieee.org
Critical infrastructures such as connected and au-tonomous vehicles, are susceptible to
cyber attacks due to their mission-critical deployment. To ensure security by design, radio …