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 …
Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
UAV-assisted IoT applications, cybersecurity threats, AI-enabled solutions, open challenges with future research directions
Unnamed Ariel Vehicle-assisted-Internet of Things (UAV-assisted IoT) applications have
emerged as a powerful integrated technology, showcasing remarkable results in many …
emerged as a powerful integrated technology, showcasing remarkable results in many …
Artificial intelligence implication on energy sustainability in Internet of Things: A survey
The massive number of Internet of Things (IoT) devices connected to the Internet is
continuously increasing. The operations of these devices rely on consuming huge amounts …
continuously increasing. The operations of these devices rely on consuming huge amounts …
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 …
[PDF][PDF] Resource allocation optimization using artificial intelligence methods in various computing paradigms: A Review
With the advent of smart devices, the demand for various computational paradigms such as
the Internet of Things, fog, and cloud computing has increased. However, effective resource …
the Internet of Things, fog, and cloud computing has increased. However, effective resource …
[HTML][HTML] Knowledge-defined networking: Applications, challenges and future work
Future 6G wireless communication systems are expected to feature intelligence and
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …
A new block-based reinforcement learning approach for distributed resource allocation in clustered IoT networks
Resource allocation and spectrum management are two major challenges in the massive
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
Deep learning based double-contention random access for massive machine-type communication
With the rapid development of 5G, massive machine-type communication is expected to
experience significant growth, leading to severe random access collisions. To address this …
experience significant growth, leading to severe random access collisions. To address this …