Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
A comprehensive survey of generative adversarial networks (GANs) in cybersecurity intrusion detection
Generative Adversarial Networks (GANs) have seen significant interest since their
introduction in 2014. While originally focused primarily on image-based tasks, their capacity …
introduction in 2014. While originally focused primarily on image-based tasks, their capacity …
Long-term mobile traffic forecasting using deep spatio-temporal neural networks
Forecasting with high accuracy the volume of data traffic that mobile users will consume is
becoming increasingly important for precision traffic engineering, demand-aware network …
becoming increasingly important for precision traffic engineering, demand-aware network …
Flow-based network traffic generation using generative adversarial networks
Flow-based data sets are necessary for evaluating network-based intrusion detection
systems (NIDS). In this work, we propose a novel methodology for generating realistic flow …
systems (NIDS). In this work, we propose a novel methodology for generating realistic flow …
Spatio-temporal analysis and prediction of cellular traffic in metropolis
Understanding and predicting cellular traffic at large-scale and fine-granularity is beneficial
and valuable to mobile users, wireless carriers, and city authorities. Predicting cellular traffic …
and valuable to mobile users, wireless carriers, and city authorities. Predicting cellular traffic …
Adversarial attacks against deep learning-based network intrusion detection systems and defense mechanisms
C Zhang, X Costa-Perez… - IEEE/ACM Transactions on …, 2022 - ieeexplore.ieee.org
Neural networks (NNs) are increasingly popular in developing NIDS, yet can prove
vulnerable to adversarial examples. Through these, attackers that may be oblivious to the …
vulnerable to adversarial examples. Through these, attackers that may be oblivious to the …
Imdiffusion: Imputed diffusion models for multivariate time series anomaly detection
Anomaly detection in multivariate time series data is of paramount importance for ensuring
the efficient operation of large-scale systems across diverse domains. However, accurately …
the efficient operation of large-scale systems across diverse domains. However, accurately …
Generative AI in mobile networks: a survey
This paper provides a comprehensive review of recent challenges and results in the field of
generative AI with application to mobile telecommunications networks. The objective is to …
generative AI with application to mobile telecommunications networks. The objective is to …
Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback
In microservice systems, the identification of root causes of anomalies is imperative for
service reliability and business impact. This process is typically divided into two phases:(i) …
service reliability and business impact. This process is typically divided into two phases:(i) …
A survey of online data-driven proactive 5G network optimisation using machine learning
In the fifth-generation (5G) mobile networks, proactive network optimisation plays an
important role in meeting the exponential traffic growth, more stringent service requirements …
important role in meeting the exponential traffic growth, more stringent service requirements …