<p>Digital image watermarking is a vital technique in the field of information security and content authentication. In watermarking, two important parameters to be considered are imperceptibility and robustness. The watermark added should not degrade the visual quality of the image. Therefore for balancing these two parameters, a watermark strength factor called alpha plays a crucial role. The optimization of these values requires tuning to perform. Existing optimization methods have constraints such as large input parameters, search space, and slow convergence. Therefore, this work proposes a hybrid optimization technique called Grey-Cuckoo Search Optimization (GCSO) to improve the balance between various characteristics of watermarking by taking advantage of both algorithms. The primary objective of the proposed work is to achieve remarkable watermarking performance in terms of various performance measures. To evaluate the performance of the proposed approach, various image-processing attacks are performed. Experimental results show that the proposed work outperformed state-of-work methods. The findings reflect the ability of Grey-Cuckoo optimized watermarking to maintain a high level of resistance along with good perceptual quality. Subsequently, two security mechanisms have been embedded with the proposed approach to secure the added watermark from unauthorized users.</p>