[HTML][HTML] Intrusion detection system in distributed cloud computing: Hybrid clustering and classification methods
K Samunnisa, GSV Kumar, K Madhavi - Measurement: Sensors, 2023 - Elsevier
Cloud Computing is popular nowadays due to its storage and data access services. Security
and privacy are prime concerns when network threats increase. Cloud computing offers …
and privacy are prime concerns when network threats increase. Cloud computing offers …
Current trends in AI and ML for cybersecurity: A state-of-the-art survey
N Mohamed - Cogent Engineering, 2023 - Taylor & Francis
This paper provides a comprehensive survey of the state-of-the-art use of Artificial
Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper …
Intelligence (AI) and Machine Learning (ML) in the field of cybersecurity. The paper …
A survey on feature selection techniques based on filtering methods for cyber attack detection
Y Lyu, Y Feng, K Sakurai - Information, 2023 - mdpi.com
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
Towards early and accurate network intrusion detection using graph embedding
Early and accurate detection of network intrusions is crucial to ensure network security and
stability. Existing network intrusion detection methods mainly use conventional machine …
stability. Existing network intrusion detection methods mainly use conventional machine …
Public cloud networks oriented deep neural networks for effective intrusion detection in online music education
The rapid growth of online music education has led to increased security risks from cyber
intrusions. This paper proposes public cloud networks oriented deep neural networks for …
intrusions. This paper proposes public cloud networks oriented deep neural networks for …
A review on challenges and future research directions for machine learning-based intrusion detection system
Research in the field of Intrusion Detection is focused on developing an efficient strategy that
can identify network attacks. One of the important strategies is to supervise the network …
can identify network attacks. One of the important strategies is to supervise the network …
Federated learning for reliable model updates in network-based intrusion detection
Abstract Machine Learning techniques for network-based intrusion detection are widely
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
adopted in the scientific literature. Besides being highly variable, network traffic behavior …
A systematic and comprehensive survey of recent advances in intrusion detection systems using machine learning: Deep learning, datasets, and attack taxonomy
Recently, intrusion detection systems (IDS) have become an essential part of most
organisations' security architecture due to the rise in frequency and severity of network …
organisations' security architecture due to the rise in frequency and severity of network …
Research of machine learning algorithms for the development of intrusion detection systems in 5G mobile networks and beyond
A Imanbayev, S Tynymbayev, R Odarchenko… - Sensors, 2022 - mdpi.com
The introduction of fifth generation mobile networks is underway all over the world which
makes many people think about the security of the network from any hacking. Over the past …
makes many people think about the security of the network from any hacking. Over the past …
Survey on Unified Threat Management (UTM) Systems for Home Networks
Home networks increasingly support important networked applications with limited
professional network administration support, while sophisticated attacks pose enormous …
professional network administration support, while sophisticated attacks pose enormous …