<p>The increasing use of artificial neural networks (ANNs) on hardware with limited resources raises issues with data secrecy, energy efficiency, and compatibility with new quantum technologies. Because conventional ANN implementations rely on irreversible logic operations, they are more susceptible to side-channel attacks and have higher power dissipation. The proposed method, a safe ANN architecture for quantum-compatible hardware platforms based on reversible logic gates is proposed. The architecture reduces information leakage by minimizing energy loss and preserving information through the use of reversible processing blocks. Furthermore, resistance to power and timing-based side-channel assaults is improved by the adoption of balanced and deterministic reversible gate designs. At the hardware level, the suggested architecture is compared to conventional irreversible ANN implementations, taking into account parameters like power consumption, delay, area overhead, and security resilience. The reversible ANN architecture dramatically lowers power dissipation while preserving computational accuracy and enhancing overall hardware security, according to experimental data.</p>