[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
R Kaur, D Gabrijelčič, T Klobučar - Information Fusion, 2023 - Elsevier
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
A review of anomaly detection strategies to detect threats to cyber-physical systems
N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …
components. CPS has experienced rapid growth over the past decade in fields as disparate …
Digitalisation and innovation in the steel industry in Poland—Selected tools of ICT in an analysis of statistical data and a case study
B Gajdzik, R Wolniak - Energies, 2021 - mdpi.com
Digital technologies enable companies to build cyber-physical systems (CPS) in Industry
4.0. In the increasingly popular concept of Industry 4.0, an important research topic is the …
4.0. In the increasingly popular concept of Industry 4.0, an important research topic is the …
Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems
Abstract Industrial Internet of Things (IIoT) networks involves heterogeneous technological
and manufacturing services and devices. The communication and data exchange …
and manufacturing services and devices. The communication and data exchange …
Artificial intelligence enabled intrusion detection systems for cognitive cyber-physical systems in industry 4.0 environment
Abstract In recent days, Cognitive Cyber-Physical System (CCPS) has gained significant
interest among interdisciplinary researchers which integrates machine learning (ML) and …
interest among interdisciplinary researchers which integrates machine learning (ML) and …
Comparative evaluation of ai-based techniques for zero-day attacks detection
Many intrusion detection and prevention systems (IDPS) have been introduced to identify
suspicious activities. However, since attackers are exploiting new vulnerabilities in systems …
suspicious activities. However, since attackers are exploiting new vulnerabilities in systems …
Deep learning techniques to detect cybersecurity attacks: a systematic mapping study
D Torre, F Mesadieu, A Chennamaneni - Empirical Software Engineering, 2023 - Springer
Context Recent years have seen a lot of attention into Deep Learning (DL) techniques used
to detect cybersecurity attacks. DL techniques can swiftly analyze massive datasets, and …
to detect cybersecurity attacks. DL techniques can swiftly analyze massive datasets, and …
Masked graph neural networks for unsupervised anomaly detection in multivariate time series
Anomaly detection has been widely used in grid operation and maintenance, machine fault
detection, and so on. In these applications, the multivariate time-series data from multiple …
detection, and so on. In these applications, the multivariate time-series data from multiple …
TrIDS: an intelligent behavioural trust based IDS for smart healthcare system
Abstract The Medical Cyber-Physical Systems (MCPS) are composed of several medical
devices and low-cost sensors for real-time diagnosis, monitoring, and decision-making …
devices and low-cost sensors for real-time diagnosis, monitoring, and decision-making …
Design-knowledge in learning plant dynamics for detecting process anomalies in water treatment plants
There exist several process-based anomaly detectors for Industrial Control Systems (ICS).
Often such detectors are built using Machine learning (ML) algorithms that do not take …
Often such detectors are built using Machine learning (ML) algorithms that do not take …