[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 …

The Shadow of Fraud: The Emerging Danger of AI-powered Social Engineering and its Possible Cure

J Yu, Y Yu, X Wang, Y Lin, M Yang, Y Qiao… - arXiv preprint arXiv …, 2024 - arxiv.org
Social engineering (SE) attacks remain a significant threat to both individuals and
organizations. The advancement of Artificial Intelligence (AI), including diffusion models and …

Federated learning-based intrusion detection system for Internet of Things

N Hamdi - International Journal of Information Security, 2023 - Springer
Intrusion detection in the Internet of Things is becoming increasingly important as the
number of connected devices grows. Machine learning algorithms can be applied to detect …

Intrusion detection and secure data storage in the cloud were recommend by a multiscale deep bidirectional gated recurrent neural network

BC Preethi, R Vasanthi, G Sugitha… - Expert Systems with …, 2024 - Elsevier
Data communication security is developing very day with the creation of cloud computing.
The imperative for robust data communication security has become increasingly evident with …

[HTML][HTML] Cybersecurity threats and mitigation measures in agriculture 4.0 and 5.0

C Maraveas, M Rajarajan, KD Arvanitis… - Smart Agricultural …, 2024 - Elsevier
The primary aim of this study was to explore cybersecurity threats in agriculture 4.0 and 5.0,
as well as possible mitigation strategies. A secondary method was employed involving …

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 …

Trustworthy Artificial Intelligence Methods for Users' Physical and Environmental Security: A Comprehensive Review

S Szymoniak, F Depta, Ł Karbowiak, M Kubanek - Applied Sciences, 2023 - mdpi.com
Artificial Intelligence is an indispensable element of the modern world, constantly evolving
and contributing to the emergence of new technologies. We meet it in everyday applications …

Anomaly-Based Intrusion Detection Model Using Deep Learning for IoT Networks

MA Alsoufi, MM Siraj, FA Ghaleb… - … in Engineering & …, 2024 - open-access.bcu.ac.uk
The rapid growth of Internet of Things (IoT) devices has brought numerous benefits to the
interconnected world. However, the ubiquitous nature of IoT networks exposes them to …

LightFIDS: Lightweight and Hierarchical Federated IDS for Massive IoT in 6G Network

A Alotaibi, A Barnawi - Arabian Journal for Science and Engineering, 2024 - Springer
IoT traffic on access networks is expected to increase significantly with the advent of 6G-
enabled massive IoT networks. Nevertheless, current intrusion detection system (IDS) …

An optimal secure defense mechanism for DDoS attack in IoT network using feature optimization and intrusion detection system

JS Prasath, VI Shyja, P Chandrakanth… - Journal of Intelligent …, 2024 - content.iospress.com
Now, the Cyber security is facing unprecedented difficulties as a result of the proliferation of
smart devices in the Internet of Things (IoT) environment. The rapid growth in the number of …