[HTML][HTML] Open RAN security: Challenges and opportunities
Abstract Open RAN (ORAN, O-RAN) represents a novel industry-level standard for RAN
(Radio Access Network), which defines interfaces that support inter-operation between …
(Radio Access Network), which defines interfaces that support inter-operation between …
Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
6G and beyond: The future of wireless communications systems
6G and beyond will fulfill the requirements of a fully connected world and provide ubiquitous
wireless connectivity for all. Transformative solutions are expected to drive the surge for …
wireless connectivity for all. Transformative solutions are expected to drive the surge for …
Imbalanced data classification: A KNN and generative adversarial networks-based hybrid approach for intrusion detection
H Ding, L Chen, L Dong, Z Fu, X Cui - Future Generation Computer Systems, 2022 - Elsevier
With the continuous emergence of various network attacks, it is becoming more and more
important to ensure the security of the network. Intrusion detection, as one of the important …
important to ensure the security of the network. Intrusion detection, as one of the important …
TSE-IDS: A two-stage classifier ensemble for intelligent anomaly-based intrusion detection system
Intrusion detection systems (IDSs) play a pivotal role in computer security by discovering
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
and repealing malicious activities in computer networks. Anomaly-based IDS, in particular …
Network abnormal traffic detection model based on semi-supervised deep reinforcement learning
The rapid development of Internet technology has brought great convenience to our
production life, and the ensuing security problems have become increasingly prominent …
production life, and the ensuing security problems have become increasingly prominent …
Intrusion detection based on autoencoder and isolation forest in fog computing
Fog Computing has emerged as an extension to cloud computing by providing an efficient
infrastructure to support IoT. Fog computing acting as a mediator provides local processing …
infrastructure to support IoT. Fog computing acting as a mediator provides local processing …
Machine learning in network anomaly detection: A survey
S Wang, JF Balarezo, S Kandeepan… - IEEE …, 2021 - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …
networks against malicious access is always challenging even though it has been studied …
Intrusion detection for cyber–physical systems using generative adversarial networks in fog environment
PF de Araujo-Filho, G Kaddoum… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Cyber-attacks cyber-physical systems (CPSs) can lead to sensing and actuation
misbehavior, severe damages to physical objects, and safety risks. Machine learning …
misbehavior, severe damages to physical objects, and safety risks. Machine learning …
Synthetic attack data generation model applying generative adversarial network for intrusion detection
Detecting a large number of attack classes accurately applying machine learning (ML) and
deep learning (DL) techniques depends on the number of representative samples available …
deep learning (DL) techniques depends on the number of representative samples available …