Intrusion detection for computer network systems has been becoming one of the most critical
tasks for network administrators today. It has an important role for organizations …

In the software design, protecting a computer system from a plethora of software attacks or
malware in the wild has been increasingly important. One branch of research to detect the …

Multi-Agent Reinforcement Learning (MARL) extends individual reinforcement learning to
enable a team of agents to collaboratively determine the global optimal policy that …

In this paper, we present a modeling and learning method to analyze the network behavior
of mobile applications based on the Android platform. Various application system sand …

The Internet of Things (IoT) is a sophisticated paradigm in which a vast number of items are
networked together. These interconnected gadgets create a network of intelligent systems …

In response to the growing cyber-attacks against governments and commercial companies
globally, Network Intrusion Detection Systems (NIDS) have been rapidly developed in …

Artificial intelligence approaches have been extremely popular, they continue to play a
major role in controlling and mitigating security threats. Information security is important …

Deep learning is an advanced model of traditional machine learning. This has the capability
to extract optimal feature representation from raw input samples. This has been applied …

L'estimation de la durée de vie utile restante (RUL) est une mesure pronostique efficace qui
prévoit l'état de santé de la machine en fonction de la modélisation de la dégradation et de …

At present, most of the meteorological prediction research is mainly aimed at one weather
parameter, and in this paper, a LSTM-GRU-multi network model is proposed to generate …