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A Review of Recent Developments on Secure Authentication Using RF Fingerprints Techniques

Yıl 2022, Cilt: 5 Sayı: 3, 278 - 303, 31.12.2022

Hüseyin Parmaksız , Cihan Karakuzu

https://doi.org/10.35377/saucis...1084024
Cited By: 1

Öz

The Internet of Things (IoT) concept is widely used today. As IoT becomes more widely adopted, the number of devices communicating wirelessly (using various communication standards) grows. Due to resource constraints, customized security measures are not possible on IoT devices. As a result, security is becoming increasingly important in IoT. It is proposed in this study to use the physical layer properties of wireless signals as an effective method of increasing IoT security. According to the literature, radio frequency (RF) fingerprinting (RFF) techniques are used as an additional layer of security for wireless devices. To prevent spoofing or spoofing attacks, unique fingerprints appear to be used to identify wireless devices for security purposes (due to manufacturing defects in the devices' analog components). To overcome the difficulties in RFF, different parts of the transmitted signals (transient/preamble/steady-state) are used.
This review provides an overview of the most recent RFF technique developments. It discusses various solution methods as well as the challenges that researchers face when developing effective RFFs. It takes a step towards the discovery of the wireless world in this context by drawing attention to the existence of software-defined radios (SDR) for signal capture. It also demonstrates how and what features can be extracted from captured RF signals from various wireless communication devices. All of these approaches' methodologies, classification algorithms, and feature classification are explained.
In addition, this study discusses how deep learning, neural networks, and machine learning algorithms, in addition to traditional classifiers, can be used. Furthermore, the review gives researchers easy access to sample datasets in this field.

Anahtar Kelimeler

iot security deep learning RF fingerprinting software-defined radio

Destekleyen Kurum

Bilecik Şeyh Edebali University Scientific Research Projects

Proje Numarası

2021-01.BŞEÜ.01-01

Kaynakça

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Yıl 2022, Cilt: 5 Sayı: 3, 278 - 303, 31.12.2022

Hüseyin Parmaksız , Cihan Karakuzu

https://doi.org/10.35377/saucis...1084024
Cited By: 1

Öz

Proje Numarası

2021-01.BŞEÜ.01-01

Kaynakça

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Toplam 111 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Yazılımı, Yazılım Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Hüseyin Parmaksız 0000-0001-8455-5625

Cihan Karakuzu 0000-0003-0569-098X

Proje Numarası 2021-01.BŞEÜ.01-01
Yayımlanma Tarihi 31 Aralık 2022
Gönderilme Tarihi 7 Mart 2022
Kabul Tarihi 11 Ekim 2022
Yayımlandığı Sayı Yıl 2022Cilt: 5 Sayı: 3

Kaynak Göster

IEEE H. Parmaksız ve C. Karakuzu, “A Review of Recent Developments on Secure Authentication Using RF Fingerprints Techniques”, SAUCIS, c. 5, sy. 3, ss. 278–303, 2022, doi: 10.35377/saucis...1084024.

Cited By

RF Signal Feature Extraction in Integrated Sensing and Communication
IET Signal Processing
https://doi.org/10.1049/2023/4251265

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