Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform

Due to the simultaneous development of DC-microgrids (DC-MGs) and the use of intelligent control, monitoring and operation methods, as well as their structure, these networks can be threatened by various cyber-attacks. Overall, a typical smart DC-MG includes battery, supercapacitors and power electronic devices, fuel cell, solar Photovoltaic (PV) systems, and loads such as smart homes, plug-in hybrid electrical vehicle (PHEV), smart sensors and network communication like fiber cable or wireless to send and receive data. Given these issues, cyber-attack detection and securing data exchanged in smart DC-MGs like CPS has been considered by experts as a significant subject in recent years. In this study, in order to detect false data injection attacks (FDIAs) in a MG system, Hilbert-Huang transform methodology along with blockchain-based ledger technology is used for enhancing the security in the smart DC-MGs with analyzing the voltage and current signals in smart sensors and controllers by extracting the signal details. Results of simulation on the different cases are considered with the objective of verifying the efficacy of the proposed model. The results offer that the suggested model can provide a more precise and robust detection mechanism against FDIA and improve the security of data exchanging in a smart DC-MG.

[1]  Taher Niknam,et al.  Cyber Attack Detection Based on Wavelet Singular Entropy in AC Smart Islands: False Data Injection Attack , 2021, IEEE Access.

[2]  Wei Chen,et al.  Distributed Resilient Filtering for Power Systems Subject to Denial-of-Service Attacks , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[3]  Mohammad Ghiasi,et al.  Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources , 2019, Energy.

[4]  Yan Zhang,et al.  Enabling Localized Peer-to-Peer Electricity Trading Among Plug-in Hybrid Electric Vehicles Using Consortium Blockchains , 2017, IEEE Transactions on Industrial Informatics.

[5]  Tomislav Dragicevic,et al.  Detection of False Data Injection Cyber-Attacks in DC Microgrids Based on Recurrent Neural Networks , 2021, IEEE Journal of Emerging and Selected Topics in Power Electronics.

[6]  Satoshi Nakamoto Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[7]  Mohammad Ghiasi,et al.  A Detailed Study for Load Flow Analysis in Distributed Power System , 2018 .

[8]  Bo Chen,et al.  Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach , 2021, IEEE Transactions on Smart Grid.

[9]  Hamid Reza Baghaee,et al.  Resilient Synchronization of Voltage/Frequency in AC Microgrids Under Deception Attacks , 2021, IEEE Systems Journal.

[10]  Guillaume Chapron,et al.  The environment needs cryptogovernance , 2017, Nature.

[11]  Pierluigi Siano,et al.  Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model , 2020 .

[12]  Lamine Mili,et al.  A Generalized False Data Injection Attacks Against Power System Nonlinear State Estimator and Countermeasures , 2018, IEEE Transactions on Power Systems.

[13]  Mohammad Ghiasi,et al.  Technical and economic evaluation of power quality performance using FACTS devices considering renewable generations , 2019, Renewable Energy Focus.

[14]  Manolis Vavalis,et al.  Blockchain based uniform price double auctions for energy markets , 2019, Applied Energy.

[15]  Walid Saad,et al.  Data Injection Attacks on Smart Grids With Multiple Adversaries: A Game-Theoretic Perspective , 2016, IEEE Transactions on Smart Grid.

[16]  Taher Niknam,et al.  False Data Injection Attack Detection based on Hilbert-Huang Transform in AC Smart Islands , 2020, IEEE Access.

[17]  Keke Gai,et al.  Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid , 2019, IEEE Transactions on Industrial Informatics.

[18]  Abdollah Kavousi-Fard,et al.  Deep learning based method for false data injection attack detection in AC smart islands , 2020, IET Generation, Transmission & Distribution.

[19]  Siddharth Suman,et al.  Investigating Overall Structure of Cyber-Attacks on Smart-Grid Control Systems to Improve Cyber Resilience in Power System , 2020 .

[20]  Henry Leung,et al.  Relaxation-based anomaly detection in cyber-physical systems using ensemble kalman filter , 2019, IET Cyper-Phys. Syst.: Theory & Appl..

[21]  Wenming Zhang,et al.  Stealthy attack detection and solution strategy for consensus-based distributed economic dispatch problem , 2018, International Journal of Electrical Power & Energy Systems.

[22]  Mohammad Ghiasi,et al.  A comparative study on common power flow techniques in the power distribution system of the Tehran metro , 2018, Tehnički glasnik.

[23]  Taher Niknam,et al.  A robust voltage and current controller of parallel inverters in smart island: A novel approach , 2021 .

[24]  Amin Hajizadeh,et al.  Localized Protection of Radial DC Microgrids With High Penetration of Constant Power Loads , 2021, IEEE Systems Journal.

[25]  Khalid Alsubhi,et al.  Cyber Attack Detection Process in Sensor of DC Micro-Grids Under Electric Vehicle based on Hilbert-Huang Transform and Deep Learning , 2020 .

[26]  Pierluigi Siano,et al.  An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data , 2019 .

[27]  Daniel Davis Wood,et al.  ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER , 2014 .

[28]  Tomislav Dragicevic,et al.  False Data Injection Cyber-Attacks Mitigation in Parallel DC/DC Converters Based on Artificial Neural Networks , 2020, IEEE Transactions on Circuits and Systems II: Express Briefs.

[29]  Aleksandr Ometov,et al.  An Overview on Blockchain for Smartphones: State-of-the-Art, Consensus, Implementation, Challenges and Future Trends , 2020, IEEE Access.

[30]  Ning Zhang,et al.  A Secure Charging Scheme for Electric Vehicles With Smart Communities in Energy Blockchain , 2019, IEEE Internet of Things Journal.

[31]  Mohammad Ghiasi,et al.  Optimal DG Placement to Find Optimal Voltage Profile Considering Minimum DG Investment Cost in Smart Neighborhood , 2019, Smart Cities.

[32]  Subhasis Thakur,et al.  Co-simulation of electricity distribution networks and peer to peer energy trading platforms , 2020 .

[33]  Wen Yu,et al.  An IoT Expert System Shell in Block-Chain Technology with ELM as Inference Engine , 2019, Int. J. Inf. Technol. Decis. Mak..

[34]  Jianhui Wang,et al.  Energy Crowdsourcing and Peer-to-Peer Energy Trading in Blockchain-Enabled Smart Grids , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[35]  Karl Henrik Johansson,et al.  Cyber security analysis of state estimators in electric power systems , 2010, 49th IEEE Conference on Decision and Control (CDC).

[36]  Pengfei Duan,et al.  Distributed Energy Management in Smart Grids Based on Cloud-Fog Layer Architecture Considering PHEVs , 2020 .

[37]  Ju Wook Jang,et al.  A Blockchain-Based Energy Trading Platform for Smart Homes in a Microgrid , 2018, 2018 3rd International Conference on Computer and Communication Systems (ICCCS).

[38]  Peng Zhou,et al.  Detecting Replay Attacks in Power Systems: A Data-Driven Approach , 2017, LSMS/ICSEE.

[39]  Zhanle Wang,et al.  An ensemble method of full wavelet packet transform and neural network for short term electrical load forecasting , 2020 .