Enhancing cybersecurity in smart grids: Deep black box adversarial attacks and quantum voting ensemble models for blockchain privacy-preserving storage

Author:

Aurangzeb Muhammad,Wang Yifei,Iqbal Sheeraz,Naveed Ausnain,Ahmed Zeeshan,Alenezi Mohammed,Shouran Mokhtar

Publisher

Elsevier BV

Reference25 articles.

1. Cyber-physical anomaly detection in microgrids using time-frequency logic formalism;Beg;IEEE Access,2021

2. Anomaly detection in smart grids using machine learning;Reddy Shabad;IECON Proc. (Industrial Electron. Conf.,2021

3. P. G and A. Kumari K, “An Introductory Review Of Anomaly Detection Methods In Smart Grids,” 2022, doi: 10.4108/eai.7-12-2021.2314604.

4. Sequential Detection of microgrid bad data via a data-driven approach combining online machine learning with statistical analysis;Huang;Front. Energy Res.,2022

5. N.I. Haque et al., “Machine Learning in Generation, Detection, and Mitigation of Cyberattacks in Smart Grid: A Survey,” 2020, [Online]. Available: http://arxiv.org/abs/2010.00661.

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