Mapping the evolution of intrusion detection in big data: A bibliometric analysis
MG Yaseen, AS Albahri - Mesopotamian Journal of Big Data, 2023 - mesopotamian.press
This study provides a comprehensive analysis of the dynamic amalgamation of intrusion
detection and big data, revealing trends and patterns within cybersecurity research. The …
detection and big data, revealing trends and patterns within cybersecurity research. The …
Enhancing cloud-based security: a novel approach for efficient cyber-threat detection using GSCSO-IHNN model
D Ramachandran, M Albathan, A Hussain, Q Abbas - Systems, 2023 - mdpi.com
Developing a simple and efficient attack detection system for ensuring the security of cloud
systems against cyberthreats is a crucial and demanding process in the present time. In …
systems against cyberthreats is a crucial and demanding process in the present time. In …
Distributed deep learning approach for intrusion detection system in industrial control systems based on big data technique and transfer learning
Industry 4.0 refers to a new generation of connected and intelligent factories that is driven by
the emergence of new technologies such as artificial intelligence, Cloud computing, Big …
the emergence of new technologies such as artificial intelligence, Cloud computing, Big …
An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems
S Muthubalaji, NK Muniyaraj, SPVS Rao… - Big Data Mining and …, 2024 - ieeexplore.ieee.org
Big data has the ability to open up innovative and ground-breaking prospects for the
electrical grid, which also supports to obtain a variety of technological, social, and financial …
electrical grid, which also supports to obtain a variety of technological, social, and financial …
CGAAD: Centrality-and Graph-Aware Deep Learning Model for Detecting Cyberattacks Targeting Industrial Control Systems in Critical Infrastructure
TNI Alrumaih, MJF Alenazi - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Industrial control systems (ICSs) are crucial in managing critical infrastructure, making their
security a paramount concern. In recent years, their widespread adoption, together with the …
security a paramount concern. In recent years, their widespread adoption, together with the …
UASDAC: An Unsupervised Adaptive Scalable DDoS Attack Classification in Large-Scale IoT Network under Concept Drift
S Saravanan, UM Balasubramanian - IEEE Access, 2024 - ieeexplore.ieee.org
Day by day, the number of devices in IoT networks is increasing, and concurrently, the size
of botnets in IoT networks is also expanding. Currently, attackers prefer IoT-based botnets to …
of botnets in IoT networks is also expanding. Currently, attackers prefer IoT-based botnets to …
Role of machine learning approach for industrial internet of things (IIoT) in cloud environment-a systematic review
The industrial internet of things (IIoT) is related to the fourth industrial revolution and
includes different applications and innovations for the conduction of industrial activities. The …
includes different applications and innovations for the conduction of industrial activities. The …
Hyperparameter Tuned Cloud Based Cyber Physical Attack Detection using Stacking Ensemble Learning
R Sinha, P Agrawal, A Rasool - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
The primary goal of this study is to analyze cyber-physical attacks on critical networks and to
examine the operation of the cyber-physical system (intrusion detection system) and how …
examine the operation of the cyber-physical system (intrusion detection system) and how …
[PDF][PDF] Enhancing Cloud-Based Security: A Novel Approach for Efficient Cyber-Threat Detection Using GSCSO-IHNN Model. Systems 2023, 11, 518
Developing a simple and efficient attack detection system for ensuring the security of cloud
systems against cyberthreats is a crucial and demanding process in the present time. In …
systems against cyberthreats is a crucial and demanding process in the present time. In …