Physical layer security for authentication, confidentiality, and malicious node detection: a paradigm shift in securing IoT networks
The pervasiveness of commercial Internet of Things (IoT) around the globe is expected to
reach significant levels with the upcoming sixth generation of mobile networks (6G) …
reach significant levels with the upcoming sixth generation of mobile networks (6G) …
Radio frequency fingerprint identification for device authentication in the internet of things
Device authentication of wireless devices at the physical layer could augment security
enforcement before fully decoding packets. At the upper layers of the stack, this is …
enforcement before fully decoding packets. At the upper layers of the stack, this is …
Overcoming data limitations: a few-shot specific emitter identification method using self-supervised learning and adversarial augmentation
Specific emitter identification (SEI) based on radio frequency fingerprinting (RFF) is a
physical layer authentication method in the field of wireless network security. RFFs are …
physical layer authentication method in the field of wireless network security. RFFs are …
Semi-supervised specific emitter identification method using metric-adversarial training
Specific emitter identification (SEI) plays an increasingly crucial and potential role in both
military and civilian scenarios. It refers to a process to discriminate individual emitters from …
military and civilian scenarios. It refers to a process to discriminate individual emitters from …
Few-shot specific emitter identification using asymmetric masked auto-encoder
Specific emitter identification (SEI) based on radio frequency fingerprint (RFF) characteristics
can be used to identify different transmitters, and the deep learning (DL)-based SEI methods …
can be used to identify different transmitters, and the deep learning (DL)-based SEI methods …
GPU-free specific emitter identification using signal feature embedded broad learning
Emerging wireless networks may suffer severe security threats due to the ubiquitous access
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …
of massive wireless devices. Specific emitter identification (SEI) is considered as one of the …
Supervised contrastive learning for RFF identification with limited samples
Radio-frequency fingerprint (RFF), which comes from the imperfect hardware, is a potential
feature to ensure the security of communication. With the development of deep learning …
feature to ensure the security of communication. With the development of deep learning …
Wisig: A large-scale wifi signal dataset for receiver and channel agnostic rf fingerprinting
RF fingerprinting leverages circuit-level variability of transmitters to identify them using
signals they send. Signals used for identification are impacted by a wireless channel and …
signals they send. Signals used for identification are impacted by a wireless channel and …
Toward length-versatile and noise-robust radio frequency fingerprint identification
Radio frequency fingerprint identification (RFFI) can classify wireless devices by analyzing
the signal distortions caused by intrinsic hardware impairments. Recently, state-of-the-art …
the signal distortions caused by intrinsic hardware impairments. Recently, state-of-the-art …
Explanation-guided backdoor attacks on model-agnostic rf fingerprinting
Despite the proven capabilities of deep neural networks (DNNs) for radio frequency (RF)
fingerprinting, their security vulnerabilities have been largely overlooked. Unlike the …
fingerprinting, their security vulnerabilities have been largely overlooked. Unlike the …