Abstract

This research introduces a novel algorithmic framework combining deep learning and block chain to create a cyber-resilient energy grid for defence satellite operations. Building on prior techniques such as LSTM, CNN, DRL, GNN, and Bayesian networks, this paper extends their use across Earth-based smart grids, aerospace systems, and military aircrafts. Addressing gaps in secure AI-based energy coordination, our design integrates zero-trust block chain authentication with federated and reinforcement learning models to ensure continuity, autonomy, and resilience. A Python implementation is presented with all required operations, functions, and libraries.

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