Mitigation of attack detection via multi-stage cyber intelligence technique in smart grid

Abstract

A smart grid is an electrical system that uses electronic communications to support two distinct data and electricity flows. This makes it possible for the system to recognize, react to, and resolve various problems. Power users of digital technology can take an active role and have the ability to cure themselves. Cybercrimes affecting the security of the smart grid include the compromise of vital client data by attackers, the spread of viruses, cybersecurity mistakes, and vulnerabilities in distributed systems. In order to identify the multi-stage cyberattacks that pose a threat to the smart grid, a novel Multi-Stage Cyber Intelligence (MSCI) technique has been developed in this work. A signal is generated by an intrusion detection system (IDS) sensor and passed through a Chebyshev filter for preprocessing in order to minimize its noise level. The risk will be identified by the security identification block, which also includes risk assessment, risk estimation, and risk identification. The Risk Identification Block finds the risk by gaining access to the Cyber Information Database. If the risk is not found, it is transmitted to the BI-LSTM Network, which verifies if it is an attack. A MATLAB simulator is used to implement the proposed approach. Evaluation criteria like Precision, F1 Score, Specificity, Accuracy, and Detective Rate have been used to assess the effectiveness of the Multi-Stage Cyber Intelligence (MSCI) technique approach that has been provided. The experimental results show that the suggested MSCI strategy has a 99% success rate, which is comparatively high when compared to the current approaches of 9.09%, 22.22%, and 47.47% for the CDS, AD-IOT, and SVM techniques, respectively.

Keywords

• Intrusion detection system (IDS)
• BI-LSTM
• Cyber information database
• Smart grid
• Multi-stage cyber intelligence