Related papers: DeepCRF: Deep Learning-Enhanced CSI-Based RF Finge…
A "wireless fingerprint" which exploits hardware imperfections unique to each device is a potentially powerful tool for wireless security. Such a fingerprint should be able to distinguish between devices sending the same message, and should…
Channel state information (CSI) based fingerprinting for WIFI indoor localization has attracted lots of attention very recently.The frequency diverse and temporally stable CSI better represents the location dependent channel characteristics…
The first step of a secure communication is authenticating legible users and detecting the malicious ones. In the last recent years, some promising schemes proposed using wireless medium network's features, in particular, channel state…
Thanks to the ubiquitous deployment of Wi-Fi hotspots, channel state information (CSI)-based Wi-Fi sensing can unleash game-changing applications in many fields, such as healthcare, security, and entertainment. However, despite one decade…
Deep learning-based RF fingerprinting offers great potential for improving the security robustness of various emerging wireless networks. Although much progress has been done in enhancing fingerprinting methods, the impact of device…
Cyber-physical systems have recently been used in several areas (such as connected and autonomous vehicles) due to their high maneuverability. On the other hand, they are susceptible to cyber-attacks. Radio frequency (RF) fingerprinting…
Fingerprinting radio frequency (RF) emitters typically involves finding unique characteristics that are featured in their received signal. These fingerprints are nuanced, but sufficiently detailed, motivating the pursuit of methods that can…
Imperfect channel state information (CSI) at the receiver, which is due to channel estimation error, is one of the main problems toward achieving optimum detection. This paper presents a deep learning based structure for combating this…
We address the critical problem of interference rejection in radio-frequency (RF) signals using a data-driven approach that leverages deep-learning methods. A primary contribution of this paper is the introduction of the RF Challenge, which…
Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others. Supervised deep learning has shown good performance in this task but using datasets not applicable to real…
Deep learning has been proven to be a powerful tool for addressing the most significant issues in cognitive radio networks, such as spectrum sensing, spectrum sharing, resource allocation, and security attacks. The utilization of deep…
Radio frequency fingerprint (RFF) is a promising device identification technology, with recent research shifting from robustness to security due to growing concerns over vulnerabilities. To date, while the security of RFF against basic…
With the rapid proliferation of edge computing, Radio Frequency Fingerprint Identification (RFFI) has become increasingly important for secure device authentication. However, practical deployment of deep learning-based RFFI models is…
In Internet of Things, where billions of devices with limited resources are communicating with each other, security has become a major stumbling block affecting the progress of this technology. Existing authentication schemes-based on…
Localization is one of the most important problems in various fields such as robotics and wireless communications. For instance, Unmanned Aerial Vehicles (UAVs) require the information of the position precisely for an adequate control…
Knowledge of information about the propagation channel in which a wireless system operates enables better, more efficient approaches for signal transmissions. Therefore, channel state information (CSI) plays a pivotal role in the system…
Indoor localization systems are most commonly based on Received Signal Strength Indicator (RSSI) measurements of either WiFi or Bluetooth-Low-Energy (BLE) beacons. In such systems, the two most common techniques are trilateration and…
We propose a software-defined testbed for Wi-Fi channel-state information (CSI) acquisition. This testbed features distributed software-defined radios (SDRs) and a custom IEEE 802.11a software stack that enables the passive collection of…
Ultra-low latency, the hallmark of fifth-generation mobile communications (5G), imposes exacting timing demands on identification as well. Current cryptographic solutions introduce additional computational overhead, which results in…
The rapid development of new generation radio interferometers such as the Square Kilometer Array (SKA) has opened up unprecedented opportunities for astronomical research. However, anthropogenic Radio Frequency Interference (RFI) from…