Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for CPS
Cyber Physical Systems (CPS) are characterized by their ability to integrate the physical and
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …
information or cyber worlds. Their deployment in critical infrastructure have demonstrated a …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
A gentle introduction to reinforcement learning and its application in different fields
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …
become one of the most important and useful technology. It is a learning method where a …
A reinforcement learning framework for optimizing age of information in RF-powered communication systems
MA Abd-Elmagid, HS Dhillon… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we study a real-time monitoring system in which multiple source nodes are
responsible for sending update packets to a common destination node in order to maintain …
responsible for sending update packets to a common destination node in order to maintain …
Experienced deep reinforcement learning with generative adversarial networks (GANs) for model-free ultra reliable low latency communication
In this paper, a novel experienced deep reinforcement learning (deep-RL) framework is
proposed to provide model-free resource allocation for ultra reliable low latency …
proposed to provide model-free resource allocation for ultra reliable low latency …
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends
Recent technological and architectural advancements in 5G networks have proven their
worth as the deployment has started over the world. Key performance elevating factor from …
worth as the deployment has started over the world. Key performance elevating factor from …
Deep reinforcement learning approach for autonomous vehicle systems for maintaining security and safety using LSTM-GAN
The success of autonomous vehicles (AV hs) depends upon the effectiveness of sensors
being used and the accuracy of communication links and technologies being employed. But …
being used and the accuracy of communication links and technologies being employed. But …
Deep learning for cybersecurity: a review
Z Chen - 2020 International Conference on Computing and …, 2020 - ieeexplore.ieee.org
With the development of Internet technology, the scale of Internet has increased
considerably, which brings with a large number of cyber-attacks. Traditional protection …
considerably, which brings with a large number of cyber-attacks. Traditional protection …
[PDF][PDF] The role of Artificial Intelligence in future technology
A Kayid - Department of Computer Science, The German …, 2020 - researchgate.net
Artificial Intelligence is the science and engineering of making intelligent machines, aimed at
providing machines with the ability to think, reach, and surpass human-level intelligence. In …
providing machines with the ability to think, reach, and surpass human-level intelligence. In …
Learning adversarial attack policies through multi-objective reinforcement learning
Abstract Deep Reinforcement Learning has shown promising results in learning policies for
complex sequential decision-making tasks. However, different adversarial attack strategies …
complex sequential decision-making tasks. However, different adversarial attack strategies …