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[HTML][HTML] Machine learning for wireless sensor networks security: An overview of challenges and issues
Energy and security are major challenges in a wireless sensor network, and they work
oppositely. As security complexity increases, battery drain will increase. Due to the limited …
oppositely. As security complexity increases, battery drain will increase. Due to the limited …
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) …
Towards scalable and channel-robust radio frequency fingerprint identification for LoRa
Radio frequency fingerprint identification (RFFI) is a promising device authentication
technique based on transmitter hardware impairments. The device-specific hardware …
technique based on transmitter hardware impairments. The device-specific hardware …
Machine learning in IoT security: Current solutions and future challenges
The future Internet of Things (IoT) will have a deep economical, commercial and social
impact on our lives. The participating nodes in IoT networks are usually resource …
impact on our lives. The participating nodes in IoT networks are usually resource …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
[HTML][HTML] Internet of Things (IoT) cybersecurity: Literature review and IoT cyber risk management
Along with the growing threat of cyberattacks, cybersecurity has become one of the most
important areas of the Internet of Things (IoT). The purpose of IoT cybersecurity is to reduce …
important areas of the Internet of Things (IoT). The purpose of IoT cybersecurity is to reduce …
DL‐IDS: a deep learning–based intrusion detection framework for securing IoT
Abstract The Internet of Things (IoT) is comprised of numerous devices connected through
wired or wireless networks, including sensors and actuators. Recently, the number of IoT …
wired or wireless networks, including sensors and actuators. Recently, the number of IoT …
Exposing the fingerprint: Dissecting the impact of the wireless channel on radio fingerprinting
Radio fingerprinting uniquely identifies wireless devices by leveraging tiny hardware-level
imperfections inevitably present in off-the-shelf radio circuitry. This way, devices can be …
imperfections inevitably present in off-the-shelf radio circuitry. This way, devices can be …
Radio frequency fingerprint identification for LoRa using deep learning
Radio frequency fingerprint identification (RFFI) is an emerging device authentication
technique that relies on the intrinsic hardware characteristics of wireless devices. This paper …
technique that relies on the intrinsic hardware characteristics of wireless devices. This paper …
Machine and deep learning for iot security and privacy: applications, challenges, and future directions
The integration of the Internet of Things (IoT) connects a number of intelligent devices with
minimum human interference that can interact with one another. IoT is rapidly emerging in …
minimum human interference that can interact with one another. IoT is rapidly emerging in …