Related papers: Open Set RF Fingerprinting Identification: A Joint…
Radio Frequency Interference (RFI) increasingly contaminates the radio astronomy spectrum, often exceeding astronomical signal amplitudes by 50-70 dB. Reliable detection and mitigation are therefore essential for studies of faint transient…
The vehicular-to-everything (V2X) technology has recently drawn a number of attentions from both academic and industrial areas. However, the openness of the wireless communication system makes it more vulnerable to identity impersonation…
Deep learning-based palmprint recognition algorithms have shown great potential. Most of them are mainly focused on identifying samples from the same dataset. However, they may be not suitable for a more convenient case that the images for…
The increasing use of the Internet of Things raises security concerns. To address this, device fingerprinting is often employed to authenticate devices, detect adversaries, and identify eavesdroppers in an environment. This requires the…
An increase in availability of Software Defined Radios (SDRs) has caused a dramatic shift in the threat landscape of legacy satellite systems, opening them up to easy spoofing attacks by low-budget adversaries. Physical-layer authentication…
Due to the diversity of attack materials, fingerprint recognition systems (AFRSs) are vulnerable to malicious attacks. It is thus important to propose effective fingerprint presentation attack detection (PAD) methods for the safety and…
The emergence of deepfake technologies has become a matter of social concern as they pose threats to individual privacy and public security. It is now of great significance to develop reliable deepfake detectors. However, with numerous face…
Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt negative sampling to discriminate different items. Training with…
Open set recognition is designed to identify known classes and to reject unknown classes simultaneously. Specifically, identifying known classes and rejecting unknown classes correspond to reducing the empirical risk and the open space…
In recent years, WiFi sensing has been recognized as a promising technology to bring respiratory monitoring into everyday homes, thanks to its contactless nature and ubiquitous availability. However, existing WiFi-based respiratory…
802.11 device fingerprinting is the action of characterizing a target device through its wireless traffic. This results in a signature that may be used for identification, network monitoring or intrusion detection. The fingerprinting method…
Deep-learning-based device fingerprinting has recently been recognized as a key enabler for automated network access authentication. Its robustness to impersonation attacks due to the inherent difficulty of replicating physical features is…
With a very rapid increase in deepfakes and digital image forgeries, ensuring the authenticity of images is becoming increasingly challenging. This report introduces a forgery detection framework that combines spatial and frequency-based…
We present an approach to identifying wireless microwave tags using radio frequency (RF) fingerprinting and machine learning. The tags are designed for low cost and simplicity, consisting of only two antennas and a single nonlinear element…
We propose a novel approach for mitigating radio frequency interference (RFI) signals in radio data using the latest advances in deep learning. We employ a special type of Convolutional Neural Network, the U-Net, that enables the…
Indoor localization is getting increasing demands for various cutting-edged technologies, like Virtual/Augmented reality and smart home. Traditional model-based localization suffers from significant computational overhead, so fingerprint…
Radio Frequency Fingerprint Identification (RFFI) has emerged as a pivotal task for reliable device authentication. Despite advancements in RFFI methods, background noise and intentional modulation features result in weak energy and subtle…
In-correlator techniques offer the possibility of identifying and/or excising radio frequency interference (RFI) from interferometric observations at much higher time and/or frequency resolution than is generally possible with the final…
Fingerprint recognition has drawn a lot of attention during last decades. Different features and algorithms have been used for fingerprint recognition in the past. In this paper, a powerful image representation called scattering…
Radio Frequency Identification (RFID) tracking may be a viable solution for defense assets that must be stored in accordance with security guidelines. However, poor sensor specificity (vulnerabilities include long range detection, spoofing,…