A review of digital twins and their application in cybersecurity based on artificial intelligence
The potential of digital twin technology is yet to be fully realised due to its diversity and
untapped potential. Digital twins enable systems' analysis, design, optimisation, and …
untapped potential. Digital twins enable systems' analysis, design, optimisation, and …
Explainable deep learning approach for advanced persistent threats (APTs) detection in cybersecurity: A review
Abstract In recent years, Advanced Persistent Threat (APT) attacks on network systems have
increased through sophisticated fraud tactics. Traditional Intrusion Detection Systems (IDSs) …
increased through sophisticated fraud tactics. Traditional Intrusion Detection Systems (IDSs) …
Explaining intrusion detection-based convolutional neural networks using shapley additive explanations (shap)
Artificial intelligence (AI) and machine learning (ML) models have become essential tools
used in many critical systems to make significant decisions; the decisions taken by these …
used in many critical systems to make significant decisions; the decisions taken by these …
[PDF][PDF] XA-GANOMALY: AN EXPLAINABLE ADAPTIVE SEMI-SUPERVISED LEARNING METHOD FOR INTRUSION DETECTION USING GANOMALY IN GLOBAL …
S Ray - ЭКОНОМИЧЕСКАЯ СРЕДА, 2023 - researchgate.net
Экономическая среда. 2023. № 1 (43) 5 женный нами метод имеет потенциал для
применения в реальной промышленности, а будущие исследования будут посвящены …
применения в реальной промышленности, а будущие исследования будут посвящены …
Detecting cyberthreats in Metaverse learning platforms using an explainable DNN
The rapid integration of the Internet of Artificial Intelligence and Internet of Things (AI-IoT)
technologies has given rise to a pivotal element of the upcoming digital era, the Metaverse …
technologies has given rise to a pivotal element of the upcoming digital era, the Metaverse …
E-XAI: Evaluating Black-Box Explainable AI Frameworks for Network Intrusion Detection
O Arreche, TR Guntur, JW Roberts, M Abdallah - IEEE Access, 2024 - ieeexplore.ieee.org
The exponential growth of intrusions on networked systems inspires new research directions
on develo** artificial intelligence (AI) techniques for intrusion detection systems (IDS). In …
on develo** artificial intelligence (AI) techniques for intrusion detection systems (IDS). In …
Machine learning algorithms for raw and unbalanced intrusion detection data in a multi-class classification problem
M Bacevicius, A Paulauskaite-Taraseviciene - Applied Sciences, 2023 - mdpi.com
Various machine learning algorithms have been applied to network intrusion classification
problems, including both binary and multi-class classifications. Despite the existence of …
problems, including both binary and multi-class classifications. Despite the existence of …
Explainable ai-based intrusion detection in the internet of things
The revolution of Artificial Intelligence (AI) has brought about a significant evolution in the
landscape of cyberattacks. In particular, with the increasing power and capabilities of AI …
landscape of cyberattacks. In particular, with the increasing power and capabilities of AI …
XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection Systems
O Arreche, T Guntur, M Abdallah - Applied Sciences, 2024 - mdpi.com
The exponential growth of network intrusions necessitates the development of advanced
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …
Enhancing iot security in 6g environment with transparent ai: Leveraging xgboost, shap and lime
The integration of IoT with cellular wireless networks is expected to deepen as cellular
technology progresses from 5G to 6G, enabling enhanced connectivity and data exchange …
technology progresses from 5G to 6G, enabling enhanced connectivity and data exchange …