Imagen de Portada

Robust Cyber security for Smart Grids: Multi-Attack Detection Using Hybrid Ensemble Models on Realistic Datasets

Fuente: Zenodo

Guardado en:

Detalles Bibliográficos
Autor principal:	UMT
Formato:	Recurso digital
Publicado:	Zenodo 2026
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Hybrid Ensemble Method for Detecting Cyber-Attacks in Water Distribution Systems Using the BATADAL Dataset
por: Ahmed, Waqas
Publicado: (2025)

Anomaly Detection of Cyber Attacks in Smart Grid Communications Based on Residual Recurrent Neural Networks
por: Long Yu, et al.
Publicado: (2025)

Smart Grid: Cyber Attacks, Critical Defense Approaches, and Digital Twin
por: Zheng, Tianming, et al.
Publicado: (2022)

Ensemble-Based Predictive Model for Cyber Attack Detection: Development and Evaluation
por: Oche Akiti Ojoje, et al.
Publicado: (2025)

Detection of Energy Consumption Cyber Attacks on Smart Devices
por: Alwaisi, Zainab, et al.
Publicado: (2024)

Unleashing the Power of Unlabeled Data: A Self-supervised Learning Framework for Cyber Attack Detection in Smart Grids
por: Zeng, Hanyu, et al.
Publicado: (2024)

An AI-Enabled Hybrid Cyber-Physical Framework for Adaptive Control in Smart Grids
por: Siddique, Muhammad, et al.
Publicado: (2025)

CRUPL: A Semi-Supervised Cyber Attack Detection with Consistency Regularization and Uncertainty-aware Pseudo-Labeling in Smart Grid
por: Dash, Smruti P., et al.
Publicado: (2025)

SG-ML: Smart Grid Cyber Range Modelling Language
por: Roomi, Muhammad M., et al.
Publicado: (2025)

An Unsupervised Adversarial Autoencoder for Cyber Attack Detection in Power Distribution Grids
por: Zideh, Mehdi Jabbari, et al.
Publicado: (2024)

Smart Grid Security: A Verified Deep Reinforcement Learning Framework to Counter Cyber-Physical Attacks
por: Maiti, Suman, et al.
Publicado: (2024)

Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization
por: Alihodžić, Adis, et al.
Publicado: (2026)

Auto-SGCR: Automated Generation of Smart Grid Cyber Range Using IEC 61850 Standard Models
por: Roomi, Muhammad M., et al.
Publicado: (2025)

Simulation of Multi-Stage Attack and Defense Mechanisms in Smart Grids
por: Sen, Omer, et al.
Publicado: (2024)

AttackMate: Realistic Emulation and Automation of Cyber Attack Scenarios Across the Kill Chain
por: Landauer, Max, et al.
Publicado: (2026)

Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids
por: Agha, Bochra Al, et al.
Publicado: (2025)

Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection
por: Vitorino, João, et al.
Publicado: (2024)

A Multi-Scale Attention-Based Attack Diagnosis Mechanism for Parallel Cyber-Physical Attacks in Power Grids
por: Ren, Junhao, et al.
Publicado: (2025)

A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids
por: Yuan, Xun, et al.
Publicado: (2023)

On the Use of Safety Critical Control for Cyber-Physical Security in the Smart Grid
por: Mohamed, Amr S., et al.
Publicado: (2023)

Enhancing Cyber-Resiliency of DER-based SmartGrid: A Survey
por: Liu, Mengxiang, et al.
Publicado: (2023)

A Hybrid CNN-LSTM Deep Learning Model for Intrusion Detection in Smart Grid
por: Alsaiari, Abdulhakim, et al.
Publicado: (2025)

Ensemble Defense System: A Hybrid IDS Approach for Effective Cyber Threat Detection
por: Alharbi, Sarah, et al.
Publicado: (2024)

Neural Network-Based Detection and Multi-Class Classification of FDI Attacks in Smart Grid Home Energy Systems
por: Sen, Varsha, et al.
Publicado: (2025)

Energy Cyber Attacks to Smart Healthcare Devices: A Testbed
por: Alwaisi, Zainab, et al.
Publicado: (2024)

A Single-Point Measurement Framework for Robust Cyber-Attack Diagnosis in Smart Microgrids Using Dual Fractional-Order Feature Analysis
por: Wang, Yifan
Publicado: (2025)

Towards Automated Generation of Smart Grid Cyber Range for Cybersecurity Experiments and Training
por: Mashima, Daisuke, et al.
Publicado: (2024)

Beetle‐Optimized Hybrid Ensemble for Multi‐Attack Classification in VANETs
por: G. SaravanaKumar, et al.
Publicado: (2025)

Joint Sensor Deployment and Physics-Informed Graph Transformer for Smart Grid Attack Detection
por: Elnour, Mariam, et al.
Publicado: (2026)

A Lightweight Edge-CNN-Transformer Model for Detecting Coordinated Cyber and Digital Twin Attacks in Cooperative Smart Farming
por: Praharaj, Lopamudra, et al.
Publicado: (2024)

Adaptive Cyber-Attack Detection in IIoT Using Attention-Based LSTM-CNN Models
por: Gueriani, Afrah, et al.
Publicado: (2025)

On Process Awareness in Detecting Multi-stage Cyberattacks in Smart Grids
por: Sen, Omer, et al.
Publicado: (2024)

Towards a Comprehensive Framework for Cyber-Incident Response Decision Support in Smart Grids
por: Sen, Omer, et al.
Publicado: (2024)

The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning
por: Abukhousa, Emad, et al.
Publicado: (2025)

Marlin: Knowledge-Driven Analysis of Provenance Graphs for Efficient and Robust Detection of Cyber Attacks
por: Li, Zhenyuan, et al.
Publicado: (2024)

Stealth Attacks Against Moving Target Defense for Smart Grid
por: Sun, Ke, et al.
Publicado: (2024)

SCEN‐SCADA Security: An Enhanced Osprey Optimization‐Based Cyber Attack Detection Model in Supervisory Control and Data Acquisition System Using Serial Cascaded Ensemble Network
por: Fatimah Yaseen Hashim Alzubaidi, et al.
Publicado: (2025)

Using Graph Theory for Improving Machine Learning-based Detection of Cyber Attacks
por: Zonneveld, Giacomo, et al.
Publicado: (2024)

Optimal Planning and Management of Hybrid Vehicles in Smart Grid
por: Seyed Mohammad Bagher Mortazavi
Publicado: (2015)

Dynamic Causal Attack Graph based Cyber-security Risk Assessment Framework for CTCS System
por: Zhang, Zikai
Publicado: (2025)