Survey on intrusion detection systems based on machine learning techniques for the protection of critical infrastructure
A Pinto, LC Herrera, Y Donoso, JA Gutierrez - Sensors, 2023 - mdpi.com
Industrial control systems (ICSs), supervisory control and data acquisition (SCADA) systems,
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
and distributed control systems (DCSs) are fundamental components of critical infrastructure …
A survey on federated learning for security and privacy in healthcare applications
Technological advances in smart devices and applications targeting the Internet of
Healthcare Things provide a perfect environment for using Machine Learning-based …
Healthcare Things provide a perfect environment for using Machine Learning-based …
Detection of real-time malicious intrusions and attacks in IoT empowered cybersecurity infrastructures
Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …
Intrusion detection is a key component of network security as an active defence technology …
DANTD: A deep abnormal network traffic detection model for security of industrial internet of things using high-order features
G Shi, X Shen, F Xiao, Y He - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the development of blockchain, artificial intelligence, and data mining technology,
abnormal network traffic data has become easy to obtain. The traffic detection model detects …
abnormal network traffic data has become easy to obtain. The traffic detection model detects …
Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks
The Internet of Things (IoT), projected to exceed 30 billion active device connections
globally by 2025, presents an expansive attack surface. The frequent collection and …
globally by 2025, presents an expansive attack surface. The frequent collection and …
Exploring edge TPU for network intrusion detection in IoT
This paper explores Google's Edge TPU for implementing a practical network intrusion
detection system (NIDS) at the edge of IoT, based on a deep learning approach. While a …
detection system (NIDS) at the edge of IoT, based on a deep learning approach. While a …
Enhancing intrusion detection in IoT networks using machine learning-based feature selection and ensemble models
A Almotairi, S Atawneh, OA Khashan… - Systems Science & …, 2024 - Taylor & Francis
Internet of Things (IoT) technology has evolved significantly, transitioning from personal
devices to powering smart cities and global deployments across diverse industries …
devices to powering smart cities and global deployments across diverse industries …
Detecting cyber threats with a Graph-Based NIDPS
BOT Wen, N Syahriza, NCW Xian, NG Wei… - … Measures for Logistics …, 2024 - igi-global.com
This chapter explores the topic of a novel network-based intrusion detection system (NIDPS)
that utilises the concept of graph theory to detect and prevent incoming threats. With …
that utilises the concept of graph theory to detect and prevent incoming threats. With …
Evaluation of contemporary intrusion detection systems for internet of things environment
Abstract Internet of Things (IoT) involves wide-ranging devices connected through the
Internet with an aim to enable coherent communication amongst them without human …
Internet with an aim to enable coherent communication amongst them without human …
Cyberpsychology: A longitudinal analysis of cyber adversarial tactics and techniques
MS Rich - Analytics, 2023 - mdpi.com
The rapid proliferation of cyberthreats necessitates a robust understanding of their evolution
and associated tactics, as found in this study. A longitudinal analysis of these threats was …
and associated tactics, as found in this study. A longitudinal analysis of these threats was …