Security and Communication Networks

Machine Learning for Security and Communication Networks 2021


Publishing date
01 Nov 2022
Status
Published
Submission deadline
01 Jul 2022

Lead Editor
Guest Editors

1Chaoyang University of Technology, Taichung, Taiwan

2National University of Singapore, Singapore


Machine Learning for Security and Communication Networks 2021

Description

In recent years, supervised machine learning methods (e.g. k-nearest neighbours, Bayes' theorem, decision tree, support vector machine, random forest, neural network, convolutional neural network, recurrent neural network, long short-term memory network, gated recurrent unit network), unsupervised machine learning methods (e.g. association rules, k-means, density-based spatial clustering of applications with noise, hierarchical clustering, deep belief networks, deep Boltzmann machine, auto-encoder, de-noising auto-encoder, etc.), reinforcement learning methods (e.g. generative adversarial network, deep Q network, trust region policy optimization, etc.), and federated learning methods have been applied to security and communication networks. For instance, machine learning methods have been used to analyze the behaviours of the data stream in networks and extract the patterns of malicious activities (packet dropping, worm propagation, jammer attacks, etc.) for generating rules in intrusion detection systems. Furthermore, time-series methods (e.g. local outlier factor, cumulative sum, adaptive online thresholding, etc.) have been proposed to retrieve the time-series features of anomalous behaviours for preventing cyber-attacks and malfunctions.

While the area of machine learning methods for security and communication networks is a rapidly expanding field of scientific research, several open research questions still need to be discussed and studied. For instance, using and improving machine learning methods for malicious activity detection, attack detection, mobile endpoint analyses, repetitive security task automation, zero-day vulnerability prevention, and other security applications are important issues in computing and communications.

This Special Issue will solicit papers across various disciplines of security and communication networks in computing and communications. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

  • New supervised machine learning methods for security and communication networks
  • New unsupervised machine learning methods for security and communication networks
  • New reinforcement learning methods for security and communication networks
  • New federated learning methods for security and communication networks
  • New optimization methods for security and communication networks

Articles

  • Special Issue
  • - Volume 2023
  • - Article ID 9840753
  • - Retraction

Retracted: Detection of DDoS Attack within Industrial IoT Devices Based on Clustering and Graph Structure Features

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9896209
  • - Retraction

Retracted: A Prediction and Evaluation Model Analysis of Enterprise Economic Management Mode Based on Neural Network Strategy

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9895458
  • - Retraction

Retracted: Multipurpose Watermarking Approach for Copyright and Integrity of Steganographic Autoencoder Models

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9892175
  • - Retraction

Retracted: The Evaluation of DDoS Attack Effect Based on Neural Network

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9820128
  • - Retraction

Retracted: Effective Bots’ Detection for Online Smartphone Game Using Multilayer Perceptron Neural Networks

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9872735
  • - Retraction

Retracted: The Construction of Interactive Classrooms in Colleges and Universities Based on Big Data Analysis and Benchmark Graph Neural Network

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9843539
  • - Retraction

Retracted: Design of Pedagogy Course Information Sharing System Based on Wireless Sensor Network

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9769165
  • - Retraction

Retracted: An Improved Image Steganography Framework Based on Y Channel Information for Neural Style Transfer

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9843154
  • - Retraction

Retracted: Optimization Model of Logistics Task Allocation Based on Genetic Algorithm

Security and Communication Networks
  • Special Issue
  • - Volume 2023
  • - Article ID 9795676
  • - Retraction

Retracted: Empirical Analysis of Enterprise Financial Management Risk Prediction in View of Associative Memory Neural Network

Security and Communication Networks
Security and Communication Networks
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Acceptance rate11%
Submission to final decision185 days
Acceptance to publication40 days
CiteScore2.600
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