Adversarial machine learning for network intrusion detection systems: A comprehensive survey

K He, DD Kim, MR Asghar - IEEE Communications Surveys & …, 2023 - ieeexplore.ieee.org
Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …

Explainable artificial intelligence (XAI) for intrusion detection and mitigation in intelligent connected vehicles: A review

CI Nwakanma, LAC Ahakonye, JN Njoku… - Applied Sciences, 2023 - mdpi.com
The potential for an intelligent transportation system (ITS) has been made possible by the
growth of the Internet of things (IoT) and artificial intelligence (AI), resulting in the integration …

[HTML][HTML] A deep learning technique for intrusion detection system using a Recurrent Neural Networks based framework

SM Kasongo - Computer Communications, 2023 - Elsevier
In recent years, the spike in the amount of information transmitted through communication
infrastructures has increased due to the advances in technologies such as cloud computing …

Anomaly based network intrusion detection for IoT attacks using deep learning technique

B Sharma, L Sharma, C Lal, S Roy - Computers and Electrical Engineering, 2023 - Elsevier
Abstract Internet of Things (IoT) applications are growing in popularity for being widely used
in many real-world services. In an IoT ecosystem, many devices are connected with each …

Explainable artificial intelligence in cybersecurity: A survey

N Capuano, G Fenza, V Loia, C Stanzione - Ieee Access, 2022 - ieeexplore.ieee.org
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being's daily
life. Despite the AI benefits, its application suffers from the opacity of complex internal …

[HTML][HTML] Securing the digital world: Protecting smart infrastructures and digital industries with artificial intelligence (AI)-enabled malware and intrusion detection

M Schmitt - Journal of Industrial Information Integration, 2023 - Elsevier
The last decades have been characterized by unprecedented technological advances,
many of them powered by modern technologies such as Artificial Intelligence (AI) and …

Unsolved problems in ml safety

D Hendrycks, N Carlini, J Schulman… - arxiv preprint arxiv …, 2021 - arxiv.org
Machine learning (ML) systems are rapidly increasing in size, are acquiring new
capabilities, and are increasingly deployed in high-stakes settings. As with other powerful …

[HTML][HTML] Deep learning for cyber threat detection in IoT networks: A review

A Aldhaheri, F Alwahedi, MA Ferrag, A Battah - Internet of Things and cyber …, 2024 - Elsevier
Abstract The Internet of Things (IoT) has revolutionized modern tech with interconnected
smart devices. While these innovations offer unprecedented opportunities, they also …

Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approach

B Sharma, L Sharma, C Lal, S Roy - Expert Systems with Applications, 2024 - Elsevier
Abstract The Internet of Things (IoT) is currently seeing tremendous growth due to new
technologies and big data. Research in the field of IoT security is an emerging topic. IoT …

Comparative analysis of intrusion detection systems and machine learning-based model analysis through decision tree

Z Azam, MM Islam, MN Huda - IEEE Access, 2023 - ieeexplore.ieee.org
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …