Image Steganography Using Particle Swarm Optimization

Any mode of communication must prioritize information security and confidentiality. The methods for using covert digital material like text, audio, video, and images to obfuscate sensitive information are commonly referred to as known as Steganography. Maintaining a fair trade-off between increased bit embedding rate, security, imperceptibility, and robustness is the major problem of steganographic system design. Therefore, with the enormous advancement in digital technology, efficient steganography algorithms are needed to convey secret information over the internet. However, compression or any other sort of noise could disclose the object that was used to conceal hidden messages, making it impossible to correctly extract them. To obtain greater security, it is necessary to apply non-traditional fundamentals for information security, such as swarm intelligence algorithms. This work proposes a steganographic method based on JPEG and the nature–inspired algorithm, Particle Swarm Optimisation (PSO) algorithm. The algorithm is used to first construct an optimal substitution matrix for modifying the undisclosed messages to make the quality of stego-images better. As well as being altered, the standard JPEG quantization table now includes extra hidden information. The modified messages are then concealed in the cover-quantized image's DCT-Coefficients’ DC-to-middle frequency components. Eventually, JPEG entropy coding is used to create a JPEG file that contains hidden messages.