Deep learning in smart grid technology: A review of recent advancements and future prospects

M Massaoudi, H Abu-Rub, SS Refaat, I Chihi… - IEEE …, 2021 - ieeexplore.ieee.org
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …

A systematic review on hybrid intrusion detection system

EM Maseno, Z Wang, H Xing - Security and Communication …, 2022 - Wiley Online Library
As computer networks keep growing at a high rate, achieving confidentiality, integrity, and
availability of the information system is essential. Intrusion detection systems (IDSs) have …

Intrusion detection for secure social internet of things based on collaborative edge computing: a generative adversarial network-based approach

L Nie, Y Wu, X Wang, L Guo, G Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The Social Internet of Things (SIoT) now penetrates our daily lives. As a strategy to alleviate
the escalation of resource congestion, collaborative edge computing (CEC) has become a …

Deep belief network integrating improved kernel-based extreme learning machine for network intrusion detection

Z Wang, Y Zeng, Y Liu, D Li - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning has become a research hotspot in the field of network intrusion detection. In
order to further improve the detection accuracy and performance, we proposed an intrusion …

Towards DDoS attack detection using deep learning approach

S Aktar, AY Nur - Computers & Security, 2023 - Elsevier
Due to the extensive use and evolution in the cyber world, different network attacks have
recently increased significantly. Distributed Denial-of-Service (DDoS) attack has become …

DMAIDPS: a distributed multi-agent intrusion detection and prevention system for cloud IoT environments

A Javadpour, P Pinto, F Ja'fari, W Zhang - Cluster Computing, 2023 - Springer
Abstract Cloud Internet of Things (CIoT) environments, as the essential basis for computing
services, have been subject to abuses and cyber threats. The adversaries constantly search …

Intrusion detection scheme with dimensionality reduction in next generation networks

K Sood, MR Nosouhi, DDN Nguyen… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Due to millions of heterogeneous physical nodes, multiple-vendor and multi-tenant domains,
and technologies etc., 5G has greatly expanded the threat landscape. Particularly from the …

A bio-inspired hybrid deep learning model for network intrusion detection

MD Moizuddin, MV Jose - Knowledge-based systems, 2022 - Elsevier
Advances in network communications have resulted in an explosion of connected device
usages in several business domains with phenomenal surge in network traffic. Though the …

[HTML][HTML] File processing security detection in multi-cloud environments: a process mining approach

X Zhang, L Cui, W Shen, J Zeng, L Du, H He… - Journal of Cloud …, 2023 - Springer
Cloud computing has gained popularity in recent years, but with its rise comes concerns
about data security. Unauthorized access and attacks on cloud-based data, applications …

GOSVM: Gannet optimization based support vector machine for malicious attack detection in cloud environment

M Arunkumar, KA Kumar - International Journal of Information Technology, 2023 - Springer
Cloud computing is the most useful computing technology for the new service progression.
Due to the distributed nature of cloud computing, security threats and cyber attacks are …