False Data Injection Attack Detection in Smart Grid Using Energy Consumption Forecasting

Abrar Mahi-al-rashid, Fahmid Hossain, Adnan Anwar and Sami Azam
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Abrar Mahi-al-rashid: Department of Mechanical and Production Engineering, Islamic University of Technology, K B Bazar Rd., Gazipur 1704, Bangladesh
Fahmid Hossain: Department of Mechanical and Production Engineering, Islamic University of Technology, K B Bazar Rd., Gazipur 1704, Bangladesh
Adnan Anwar: School of IT, Deakin University, 75 Pigdons Rd., Waurn Ponds, Geelong 3216, Australia
Sami Azam: College of Engineering, IT and Environment, Charles Darwin University, Casuarina 0810, Australia

Energies, 2022, vol. 15, issue 13, 1-17

Abstract: Supervisory Control and Data Acquisition (SCADA) systems are essential for reliable communication and control of smart grids. However, in the cyber-physical realm, it becomes highly vulnerable to cyber-attacks like False Data Injection (FDI) into the measurement signal which can circumvent the conventional detection methods and interfere with the normal operation of grids, which in turn could potentially lead to huge financial losses and can have a large impact on public safety. It is imperative to have an accurate state estimation of power consumption for further operational decision-making.This work presents novel forecasting-aided anomaly detection using an CNN-LSTM based auto-encoder sequence to sequence architecture to combat against false data injection attacks. We further present an adaptive optimal threshold based on the consumption patterns to identify abnormal behaviour. Evaluation is performed on real-time energy demand consumption data collected from the Australian Energy Market Operator. An extensive experiment shows that the proposed model outperforms other benchmark algorithms in not only improving the data injection attack (95.43%) but also significantly reducing the false positive rate.

Keywords: smart grid; deep learning; auto-encoder; false data injection; cyber security; anomaly detection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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