Research on User Abnormal Behavior Recognition Model for Water Economy Operating System Based on Transformer DOI
Maolin Tang, Gang Liu,

Zhenbang He

et al.

Published: June 21, 2024

Language: Английский

HGCNN-LSTM: A Data-driven Approach for Cyberattack Detection in Cyber-Physical Systems DOI

S. Abinash,

N. Srivatsan,

S. K. Hemachandran

et al.

SN Computer Science, Journal Year: 2025, Volume and Issue: 6(1)

Published: Jan. 7, 2025

Language: Английский

Citations

2
Securing the grid: A comprehensive analysis of cybersecurity challenges in PMU-based cyber-physical power networks DOI
Bilkisu Jimada-Ojuolape, Jiashen Teh, Ching‐Ming Lai

et al.

Electric Power Systems Research, Journal Year: 2024, Volume and Issue: 233, P. 110509 - 110509

Published: May 25, 2024

Language: Английский

Citations

11
Key-Exchange Convolutional Auto-Encoder for Data Augmentation in Early Knee Osteoarthritis Classification DOI
Zhe Wang, Aladine Chetouani, Rachid Jennane

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

7
Stochastic Gradient Boosted Distributed Decision Trees Security Approach for Detecting Cyber Anomalies and Classifying Multiclass Cyber-Attacks DOI
J. C. Sekhar, Priyanka Raina, Ashok Kumar Nanda

et al.

Computers & Security, Journal Year: 2025, Volume and Issue: unknown, P. 104320 - 104320

Published: Jan. 1, 2025

Language: Английский

Citations

0
Semi-supervised federated learning for collaborative security threat detection in control system for distributed power generation DOI
Yuan-Fang Li,

Yuancheng Li

Engineering Applications of Artificial Intelligence, Journal Year: 2025, Volume and Issue: 148, P. 110374 - 110374

Published: March 5, 2025

Language: Английский

Citations

0
Advancements in Grid Resilience: Recent Innovations in AI-Driven Solutions DOI Creative Commons

Sana Hafez,

Mohammad Alkhedher, Mohamed Ramadan

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105042 - 105042

Published: April 1, 2025

Language: Английский

Citations

0
Digital twins for sustainable design and management of smart city buildings and municipal infrastructure DOI

Zhiwei Tan,

Z. Li

Sustainable Energy Technologies and Assessments, Journal Year: 2024, Volume and Issue: 64, P. 103682 - 103682

Published: Feb. 29, 2024

Language: Английский

Citations

3
Optimizing CNN-LSTM for the Localization of False Data Injection Attacks in Power Systems DOI Creative Commons
Zhuo Li,

Yaobin Xie,

Rongkuan Ma

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(16), P. 6865 - 6865

Published: Aug. 6, 2024

As the informatization of power systems advances, secure operation faces various potential network attacks and threats. The false data injection attack (FDIA) is a common mode that can lead to abnormal system operations serious economic losses by injecting into terminal links or devices. current research on FDIA primarily focuses detecting its existence, but there relatively little localization attacks. To address this challenge, study proposes novel method (GA-CNN-LSTM) combines convolutional neural networks (CNNs), long short-term memory (LSTM), genetic algorithm (GA) accurately locate attacked bus line. This utilizes CNN extract local features LSTM with time series information global features. It integrates deeply explore complex patterns dynamic changes in data, effectively optimize hyperparameters using GA ensure an optimal performance model. Simulation experiments were conducted IEEE 14-bus 118-bus test systems. results indicate GA-CNN-LSTM achieved F1 scores for location identification 99.71% 99.10%, respectively, demonstrating superior compared other methods.

Language: Английский

Citations

3
A Novel ConvXGBoost Method for Detection and Identification of Cyberattacks on Grid-Connected Photovoltaic (PV) Inverter System DOI Creative Commons
Sai Nikhil Vodapally, Mohd. Hasan Ali

Computation, Journal Year: 2025, Volume and Issue: 13(2), P. 33 - 33

Published: Feb. 1, 2025

The integration of solar Photovoltaic (PV) systems into the AC grid poses stability challenges, especially with increasing inverter-based resources. For an efficient operation system, smart grid-forming inverters need to communicate Supervisory Control and Data Acquisition (SCADA) system. However, Internet-of-Things devices that SCADA make these vulnerable. Though many researchers proposed Artificial-Intelligence-based detection strategies, identification location attack is not considered by strategies. To overcome this drawback, paper proposes a novel Convolution extreme gradient boosting (ConvXGBoost) method for only detecting Denial Service (DoS) False Injection (FDI) attacks but also identifying component system was compromised. model compared existing Neural Network (CNN) decision tree (DT) Simulation results demonstrate effectiveness both PV fuel cell (PV-FC) systems. example, accuracy 99.25% 97.76% CNN 99.12% DT during DoS on Moreover, can detect identify faster than other models.

Language: Английский

Citations

0
Local-Global Routing Between Capsules for Hyperspectral Image Classification With Noisy Labels DOI
Heng Zhou, Ping Zhong

Digital Signal Processing, Journal Year: 2025, Volume and Issue: unknown, P. 105294 - 105294

Published: May 1, 2025

Language: Английский

Citations

0