A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
IoT security techniques based on machine learning: How do IoT devices use AI to enhance security?
The Internet of things (IoT), which integrates a variety of devices into networks to provide
advanced and intelligent services, has to protect user privacy and address attacks such as …
advanced and intelligent services, has to protect user privacy and address attacks such as …
The role of artificial intelligence and machine learning in wireless networks security: Principle, practice and challenges
Security is one of the biggest challenges concerning networks and communications. The
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
problem becomes aggravated with the proliferation of wireless devices. Artificial Intelligence …
Role of machine learning and deep learning in securing 5G-driven industrial IoT applications
Abstract The Internet of Things (IoT) connects millions of computing devices and has set a
stage for future technology where industrial use cases like smart cities and smart houses will …
stage for future technology where industrial use cases like smart cities and smart houses will …
Security threats and artificial intelligence based countermeasures for internet of things networks: a comprehensive survey
The Internet of Things (IoT) has emerged as a technology capable of connecting
heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily …
heterogeneous nodes/objects, such as people, devices, infrastructure, and makes our daily …
IoT vulnerability assessment for sustainable computing: threats, current solutions, and open challenges
Over the last few decades, sustainable computing has been widely used in areas like social
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …
computing, artificial intelligence-based agent systems, mobile computing, and Internet of …
PHY-layer spoofing detection with reinforcement learning in wireless networks
L Xiao, Y Li, G Han, G Liu… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
In this paper, we investigate the PHY-layer authentication that exploits radio channel
information (such as received signal strength indicators) to detect spoofing attacks in …
information (such as received signal strength indicators) to detect spoofing attacks in …
Security in mobile edge caching with reinforcement learning
Mobile edge computing usually uses caching to support multimedia contents in 5G mobile
Internet to reduce the computing overhead and latency. Mobile edge caching (MEC) …
Internet to reduce the computing overhead and latency. Mobile edge caching (MEC) …
Reinforcement learning-based NOMA power allocation in the presence of smart jamming
Nonorthogonal multiple access (NOMA) systems are vulnerable to jamming attacks,
especially smart jammers who apply programmable and smart radio devices such as …
especially smart jammers who apply programmable and smart radio devices such as …