UAV Application With XAI and Soft Computing Methods to Protect Privacy of Power-Data in Smart Grids

Power grids, energy generation plants, and energy distribution centres are vulnerable to cyberattacks, which can cause economic damage, disrupt power supply, and can also compromise community safety. In order to avoid the privacy leakage and data loss of multi-located power data, a privacy protection model using UAV networks, explainable AI (XAI) and soft computing is proposed in this article. UAVs are utilized to gather and monitor data from energy infrastructure. This data is very sensitive in nature and the proposed two-level authentication mechanism ensures protection of data from unauthorized access. XAI enhances the data security by analyzing the anomalies or unusual patterns in power data. An encryption method based on chaotic sequence is developed for preventing data leakage. The least squares method is used to assign weights to evaluate the privacy risk of multi-scenario power data. Then a composite chaotic sequence is generated using one and two dimensional logistic chaotic systems for safety of the data. The chaotic sequence encryption process is analyzed, and the differential privacy technology is integrated to devise the privacy protection of power data located at multiple locations. Together, these advanced technologies present a framework which is highly secure and responsive for managing power-data. The experimental results show that the proposed method has strong anti-attack and security policy to avoid the privacy leakage and data loss of multi-scenario power-data. By utilizing advanced technologies such as UAV networks, XAI and multi-level authentication with Chaotic sequence, this research work has offered a secure, simple, and resilient framework to manage and protect energy data from unauthorized access.