Radio frequency communication technology has not only greatly improved public network service, but also developed a new technological route for indoor navigation service. However, there is a gap between the precision and accuracy of indoor navigation...
With the advancement of 5G and the Internet of Things (IoT), traditional upper-layer authentication mechanisms are vulnerable to attacks, while quantum computing threatens cryptographic security. Radio frequency fingerprint identification (RFFI) offe...
Radio frequency fingerprint identification (RFFI) leverages the unique characteristics of radio signals resulting from inherent hardware imperfections for identification, making it essential for applications in telecommunications, cybersecurity, and...
The open nature of the wireless channel makes the drone communication vulnerable to adverse spoofing attacks, and the radio frequency fingerprint (RFF) identification is promising in effectively safeguarding the access security for drones. Since dron...
Utilizing a multi-frame signal (MFS) rather than a single-frame signal (SFS) for radio frequency fingerprint authentication (RFFA) shows the advantage of higher accuracy. However, previous studies have often overlooked the associated security threats...
As a typical representative of complex networks, the Internet of Vehicles (IoV) is more vulnerable to malicious attacks due to the mobility and complex environment of devices, which requires a secure and efficient authentication mechanism. Radio freq...
Radio Frequency Fingerprint Identification (RFFI) is a promising device authentication technique that utilizes inherent hardware flaws in transmitters to achieve device identification, thus effectively maintaining the security of the Internet of Thin...
The fifth-generation (5G) mobile cellular network is vulnerable to various security threats. Radio frequency fingerprint (RFF) identification is an emerging physical layer authentication technique which can be used to detect spoofing and distributed...
Radio frequency fingerprint identification (RFFI) based on physical-layer characteristics provides a reliable solution for secure authentication of Internet of Things (IoT) devices. Deep neural networks have demonstrated strong capability in improvin...
In recent years, Dedicated Short-Range Communication (DSRC) vehicle interconnection technology has achieved mature development and broad applications, which is the key Vehicle to Everything (V2X) technology to realize transport intelligence. However,...
In a frequency hopping spread spectrum (FHSS) network, the hopping pattern plays an important role in user authentication at the physical layer. However, recently, it has been possible to trace the hopping pattern through a blind estimation method fo...
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...
Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) trans...
As IoT (internet of things) devices grow in prominence, safeguarding them from cyberattacks is becoming a pressing challenge. To bootstrap IoT security, device identification or authentication is crucial for establishing trusted connections among dev...
Hardware Trojans (HTs) pose a security threat to the Internet of Things (IoT). Attackers can take control of devices in IoT through HTs, which seriously jeopardize the security of many systems in transportation, finance, healthcare, etc. Since subtle...
The automatic dependent surveillance broadcast (ADS-B) system is one of the key components of the next generation air transportation system (NextGen). ADS-B messages are transmitted in unencrypted plain text. This, however, causes significant securit...
Radio frequency fingerprinting (RFF) methods are becoming more and more popular in the context of identifying genuine transmitters and distinguishing them from malicious or non-authorized transmitters, such as spoofers and jammers. RFF approaches hav...
Radio Frequency Fingerprinting (RFF) would be a promising Physical Layer Security (PLS) solution for the Internet of Things (IoT) that requires robust, low-overhead security techniques. However, practical implementation of RFF may pose challenges, in...
With the continuous development of science and engineering technology, our society has entered the era of the mobile Internet of Things (MIoT). MIoT refers to the combination of advanced manufacturing technologies with the Internet of Things (IoT) to...
In this paper, a light-weight radio frequency fingerprinting identification (RFFID) scheme that combines with a two-layer model is proposed to realize authentications for a large number of resource-constrained terminals under the mobile edge computin...
Radio frequency (RF) fingerprinting, as an emerging physical layer security technology, demonstrates significant potential in the field of Internet of Things (IoT) security. However, most existing methods operate under a ‘closed-set’ assu...
Internet of Things (IoT) technology is widely used in new power systems, and it also provides many new modes for network attacks. Illegal terminal device identification is also a significant topic in the field of wireless authentication technology. S...
The research domain of device-free localization (DFL) is centered on the study of localization techniques which do not require targets to wear any kind of device. Passive radio mapping or passive fingerprinting is an example of a training-based DFL t...
This is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for s...
As the development of low-altitude economies and aerial countermeasures continues, the safety of unmanned aerial vehicles becomes increasingly critical, making emitter identification in remote sensing practices more essential. Effective recognition o...
Aiming at the lack of publicly available datasets of satellite Specific Emitter Identification (SEI) and the problem of insufficient data under multi-receiver conditions, this paper constructs a multi-receiver one-dimensional I/Q dataset for Iridium...
Specific emitter identification (SEI), which classifies radio transmitters by extracting hardware-intrinsic radio frequency fingerprints (RFFs), faces critical challenges in noise robustness, generalization under limited training data and class imbal...
Radio frequency fingerprint (RFF) identification represents a promising technique for lightweight device authentication. However, current research on RFF primarily focuses on the close-set recognition assumption. Moreover, the high computational comp...
Unmanned aerial vehicles (UAVs) are now readily available worldwide and users can easily fly them remotely using smart controllers. This has created the problem of keeping unauthorized UAVs away from private or sensitive areas where they can be a per...
With the increasing demand for intelligent traffic management and road network intelligent information services, the vehicular ad hoc networks (VANETs) combined with information of air, space and ground have outstanding advantages in coverage, reliab...
The proliferation of radio frequency (RF) devices in contemporary society, especially in the fields of smart homes, Internet of Things (IoT) gadgets, and smartphones, underscores the urgent need for robust identification methods to strengthen cyberse...
To improve communication stability, more wireless devices transmit multi-modal signals while operating. The term ‘modal’ refers to signal waveforms or signal types. This poses challenges to traditional specific emitter identification (SEI...
Deep learning (DL)-based specific emitter identification (SEI) technique can automatically extract radio frequency (RF) fingerprint features in RF signals to distinguish between legal and illegal devices and enhance the security of wireless network....
LoRa enables long-range communication for Internet of Things (IoT) devices, especially those with limited resources and low power requirements. Consequently, LoRa has emerged as a popular choice for numerous IoT applications. However, the security of...
With the rapid development of the internet of things (IoT), hundreds of millions of IoT devices, such as smart home appliances, intelligent-connected vehicles, and wearable devices, have been connected to the network. The open nature of IoT makes it...
Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bur...
Radio Frequency Fingerprinting (RFF) refers to the technique for identifying and classifying wireless devices on the basis of their physical characteristics, which appear in the digital signal transmitted in space. Small differences in the radio freq...
The rapid evolution of drone technology has introduced unprecedented challenges in security, particularly concerning the threat of unconventional drone and swarm attacks. In order to deal with threats, drones need to be classified by intercepting the...
With the rapid development of the unmanned aerial vehicles (UAVs) industry, there is increasing demand for UAV surveillance technology. Automatic Dependent Surveillance-Broadcast (ADS-B) provides accurate monitoring of UAVs. However, the system canno...
Radio frequency fingerprinting (RFF) is one of the communication network’s security techniques based on the identification of the unique features of RF transient signals. However, extracting these features could be burdensome, due to the nonsta...
In an era where IT security has paramount importance, the identification of devices holds a significance comparable to that of individuals. With the pervasive adoption of wireless technology, understanding the informational content within wireless da...
Initially introduced almost thirty years ago for the express purpose of providing electronic warfare systems the capabilities to detect, characterize, and identify radar emitters, Specific Emitter Identification (SEI) has recently received a lot of a...
Radio-frequency (RF) emitter recognition is a physical-layer tool for wireless security, but recognition accuracy often degrades when the acquisition domain changes. A deployed receiver must also reject unseen emitters and later register novel identi...
Unmanned aerial vehicle (UAV) identification in edge environments requires both high classification accuracy and efficient real-time deployment on lightweight hardware. This study presents LUMEN, a Lightweight UAV Multi-Enhanced Network designed for...
The use of wireless sensor networks (WSNs) in critical applications such as environmental monitoring, smart agriculture, and industrial automation has created significant security concerns, particularly due to the broadcasting nature of wireless comm...
Specific emitter identification (SEI) techniques are often used in civilian and military spectrum-management operations, and they are also applied to support the security and authentication of wireless communication. In this letter, a new SEI method...
Radio Frequency Machine Learning (RFML) has in recent years become a popular method for performing a variety of classification tasks on received signals. Among these tasks is Specific Emitter Identification (SEI), which seeks to associate a received...
Specific emitter identification (SEI) methods based on deep learning (DL) have effectively addressed complex, multi-dimensional signal recognition tasks by leveraging deep neural networks. However, this advancement introduces challenges such as model...
Device identification based on radio frequency fingerprinting is widely used to improve the security of Internet of Things systems. However, noise and acquisition inconsistencies in raw radio frequency signals can affect the effectiveness of classifi...
The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are bat...
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