相关论文: Erasing Radio Frequency Fingerprints via Active Ad…

Fingerprint recognition requires a minimal effort from the user, does not capture other information than strictly necessary for the recognition process, and provides relatively good performance. A critical step in fingerprint identification…

Identity authentication is crucial for ensuring the information security of wireless communication. Radio frequency (RF) fingerprinting techniques provide a prom-ising supplement to cryptography-based authentication approaches but rely on…

Indoor localization is a supporting technology for a broadening range of pervasive wireless applications. One promis- ing approach is to locate users with radio frequency fingerprints. However, its wide adoption in real-world systems is…

Radio Frequency Fingerprinting (RFF) is one of the promising passive authentication approaches for improving the security of the Internet of Things (IoT). However, with the proliferation of low-power IoT devices, it becomes imperative to…

The widespread adoption of voice-activated systems has modified routine human-machine interaction but has also introduced new vulnerabilities. This paper investigates the susceptibility of automatic speech recognition (ASR) algorithms in…

Although federated learning improves privacy of training data by exchanging local gradients or parameters rather than raw data, the adversary still can leverage local gradients and parameters to obtain local training data by launching…

This paper proposes passive WiFi indoor localization. Instead of using WiFi signals received by mobile devices as fingerprints, we use signals received by routers to locate the mobile carrier. Consequently, software installation on the…

Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being used in any indoor…

Connected teleoperated robotic systems play a key role in ensuring operational workflows are carried out with high levels of accuracy and low margins of error. In recent years, a variety of attacks have been proposed that actively target…

Radio Frequency Identification (RFID) is appearing as a favorite technology for automated identification, which can be widely applied to many applications such as e-passport, supply chain management and ticketing. However, researchers have…

As the rapid proliferation of on-body Internet of Things (IoT) devices, their security vulnerabilities have raised serious privacy and safety issues. Traditional efforts to secure these devices against impersonation attacks mainly rely on…

In light of the growing concerns regarding the unauthorized use of facial recognition systems and its implications on individual privacy, the exploration of adversarial perturbations as a potential countermeasure has gained traction.…

This work introduces DeepCRF, a deep learning framework designed for channel state information-based radio frequency fingerprinting (CSI-RFF). The considered CSI-RFF is built on micro-CSI, a recently discovered radio-frequency (RF)…

Trusted identification is critical to secure IoT devices. However, the limited memory and computation power of low-end IoT devices prevent the direct usage of conventional identification systems. RF fingerprinting is a promising technique…

Frequency spectrum has played a significant role in learning unique and discriminating features for object recognition. Both low and high frequency information present in images have been extracted and learnt by a host of representation…

Radio frequency interference (RFI) is the principal factor limiting the sensitivities of radio telescopes, particularly at frequencies below 1 GHz. I present a conceptually new approach to mitigation of RFI in interferometric data. This has…

RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a potential solution for automated network access authentication. Traditional approaches are commonly susceptible to the domain adaptation…

Radio Frequency Identification (RFID) systems are among the most widespread computing technologies with technical potential and profitable opportunities in numerous applications worldwide. Further, RFID is the core technology behind the…

Website Fingerprinting (WF) is a type of traffic analysis attack that enables a local passive eavesdropper to infer the victim's activity, even when the traffic is protected by a VPN or an anonymity system like Tor. Leveraging a…

Recently deep neural networks (DNNs) have achieved significant success in real-world image super-resolution (SR). However, adversarial image samples with quasi-imperceptible noises could threaten deep learning SR models. In this paper, we…