This paper proposes a new steganography framework utilizing Particle Swarm Optimization (PSO) to improve the process of embedding and extraction for safe data communication. The focus here is to tackle the issues with the standard steganography approaches, that have to deal with a trade-off between the capacity of embedding, quality of stego images and security of stego images. Here, the developed PSO-LSB steganography scheme provides a novel method for pixel selection of secret message embedding pixel position to enhance invisibility while preserving data fidelity. The refinement is a three step methodology where we first hash the message, then use PSO with hash input as seed to find a list of Least Significant Bits (LSB) pixel locations where bits abe embedded. This in turn ensures that the selected pixels are placed far apart enough so as to reduce the chances of detection and at the same time, the quality of the cover image is retained. Here embedding algorithm simply hides our secret message and metadata in cover image which gives stego image then to transmit. The secret message is correctly extracted with the proposed extraction algorithm as soon as the stego image is received which reads the hash from the stego image header and regenerates the list of pixel locations successfully with the help of PSO. The computed hash is then compared to the header hash to verify the integrity of the received message. From the experimental results on a standard dataset ‘The USC-SIPI Image Database’ we show that the proposed PSO-LSB method performs better than other existing algorithms. Higher quality and robustness of the image are appreciated through this, demonstrating 7.39% enhancement in Peak Signal-to-Noise Ratio (PSNR) and 61.36% MSE reduction concerning conventional or LSB and Goldbach LSB algorithms. The study justifies the scope of PSO towards the optimization of steganographic methods to yield more secure and faster covert communication channel.