Aerospace integrated networks innovation for empowering 6G: A survey and future challenges

D Zhou, M Sheng, J Li, Z Han - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
The ever-increasing demand for ubiquitous and differentiated services at anytime and
anywhere emphasizes the necessity of aerospace integrated networks (AINs) which consist …

A survey on space-air-ground-sea integrated network security in 6G

H Guo, J Li, J Liu, N Tian, N Kato - … Communications Surveys & …, 2021 - ieeexplore.ieee.org
Space-air-ground-sea integrated network (SAGSIN), which integrates satellite
communication networks, aerial networks, terrestrial networks, and marine communication …

[HTML][HTML] Machine learning and deep learning methods for intrusion detection systems: A survey

H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …

An evaluation of anomaly detection and diagnosis in multivariate time series

A Garg, W Zhang, J Samaran… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Several techniques for multivariate time series anomaly detection have been proposed
recently, but a systematic comparison on a common set of datasets and metrics is lacking …

Deep learning for anomaly detection: A survey

R Chalapathy, S Chawla - arxiv preprint arxiv:1901.03407, 2019 - arxiv.org
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …

Ten challenges in advancing machine learning technologies toward 6G

N Kato, B Mao, F Tang, Y Kawamoto… - IEEE Wireless …, 2020 - ieeexplore.ieee.org
As the 5G standard is being completed, academia and industry have begun to consider a
more developed cellular communication technique, 6G, which is expected to achieve high …

Deep learning-based intrusion detection systems: a systematic review

J Lansky, S Ali, M Mohammadi, MK Majeed… - IEEE …, 2021 - ieeexplore.ieee.org
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …

[HTML][HTML] A survey of deep learning methods for cyber security

DS Berman, AL Buczak, JS Chavis, CL Corbett - Information, 2019 - mdpi.com
This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …

N-baiot—network-based detection of iot botnet attacks using deep autoencoders

Y Meidan, M Bohadana, Y Mathov… - IEEE Pervasive …, 2018 - ieeexplore.ieee.org
The proliferation of IoT devices that can be more easily compromised than desktop
computers has led to an increase in IoT-based botnet attacks. To mitigate this threat, there is …

[HTML][HTML] An insider data leakage detection using one-hot encoding, synthetic minority oversampling and machine learning techniques

T Al-Shehari, RA Alsowail - Entropy, 2021 - mdpi.com
Insider threats are malicious acts that can be carried out by an authorized employee within
an organization. Insider threats represent a major cybersecurity challenge for private and …