The rapid growth of digital communication necessitates robust methods to secure sensitive data, particularly in video-based media. Being steganographic ways, similar as Least Significant Bit (LSB) and Discrete Cosine transfigure (DCT), face challenges in embedding capacity, computational complexity, and vulnerability to attacks. This paper proposes a novel video steganography framework leveraging Discrete Wavelet Transform (DWT) to enhance embedding capacity while reducing complexity. The methodology integrates Huffman encoding for lossless compression of secret data and employs the YUV color space to exploit luminance (Y) components, ensuring imperceptibility. By embedding data in the high-frequency subbands (LH and HL) of 1-D DWT decomposition, the model minimizes visual distortion. Experimental evaluations using standard test videos (Lena, Baboon, Nature) demonstrate superior performance with Peak Signal-to-Noise Ratio (PSNR) values exceeding 73 dB, Signal-to-Noise Ratio (SNR) above 68 dB, and Mean Square Error (MSE) below 0.0027, confirming high visual quality. Comparative analysis against LSB and DCT-based methods reveals enhanced security, higher payload capacity (up to 512 bytes per frame), and reduced computational overhead. The proposed approach effectively balances embedding efficiency, robustness, and simplicity, addressing critical limitations in existing techniques. This work contributes to advancing secure real-time communication systems by optimizing the trade-off between data concealment capacity and computational feasibility.