[HTML][HTML] Securing modern power systems: Implementing comprehensive strategies to enhance resilience and reliability against cyber-attacks

S Abdelkader, J Amissah, S Kinga, G Mugerwa… - Results in …, 2024 - Elsevier
Recent technological advancements in the energy sector, such as the proliferation of electric
vehicles, and smart power electronic devices, have substantially increased the demand for …

Hybrid privacy preserving federated learning against irregular users in next-generation Internet of Things

A Yazdinejad, A Dehghantanha, G Srivastava… - Journal of Systems …, 2024 - Elsevier
While federated learning (FL) is a well-known privacy-preserving (PP) solution, recent
studies demonstrate that it still has privacy problems and vulnerabilities, particularly in the …

Taxonomy of deep learning-based intrusion detection system approaches in fog computing: a systematic review

S Najafli, A Toroghi Haghighat, B Karasfi - Knowledge and Information …, 2024 - Springer
Abstract The Internet of Things (IoT) has been used in various aspects. Fundamental
security issues must be addressed to accelerate and develop the Internet of Things. An …

Federated quantum-based privacy-preserving threat detection model for consumer internet of things

D Namakshenas, A Yazdinejad… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) has significantly impacted the evolution of consumer-oriented
smart environments, primarily due to its capacity for transformative device-to-device …

Securing data and preserving privacy in cloud IoT-based technologies an analysis of assessing threats and develo** effective safeguard

M Pathak, KN Mishra, SP Singh - Artificial Intelligence Review, 2024 - Springer
Abstract The Internet of Things (IoT) is a powerful technology adopted in various industries.
Applications of the IoT aim to enhance automation, productivity, and user comfort in a cloud …

A hypertuned lightweight and scalable LSTM model for hybrid network intrusion detection

A Bibi, GA Sampedro, A Almadhor, AR Javed, T Kim - Technologies, 2023 - mdpi.com
Given the increasing frequency of network attacks, there is an urgent need for more effective
network security measures. While traditional approaches such as firewalls and data …

An explainable multi-modal model for advanced cyber-attack detection in industrial control systems

S Bahadoripour, H Karimipour, AN Jahromi, A Islam - Internet of Things, 2024 - Elsevier
Abstract The convergence of Industrial Control Systems (ICS) and intelligent Internet of
Things (IoT) technologies has rendered ICS more vulnerable to a growing range of cyber …

An adaptive neural network approach for resilient leader-following consensus control of multi-agent systems under cyber-attacks

M Mamoon, G Mustafa, N Iqbal, M Rehan, I Ahmed… - ISA transactions, 2024 - Elsevier
This paper addresses the dynamic neural networks (DNNs) based resilient leader-following
consensus control of multi-agent systems (MASs) under unidentified false data injection …

Self-training of cyber-threat classification model with threat-payload centric augmentation

JY Kim, HY Kwon - IEEE Transactions on Industrial Informatics, 2024 - ieeexplore.ieee.org
Deep learning (DL)-based threat classification has been investigated for effective analysis of
threat events to minimize the human's resources in security operation centers (SOC) …

Cyberattacks on the Maritime Sector: A Literature Review

S Symes, E Blanco-Davis, T Graham, J Wang… - Journal of Marine …, 2024 - Springer
This study is an investigation into cyberattacks on autonomous vessels, focusing on
previous “real-world” cyberattacks and their consequences. The future of commercial and …