Digitization is the process by which information is packaged into discrete bits that can be individually addressed. This makes the information machine-readable. The two most crucial factors in today’s world, when everyone is going toward digitization, are data protection and risk management. The transmitted data must be secured against any malicious attackers. Cryptography and steganography are the techniques for addressing the data-hiding process. Unlike cryptography, which transfers data in an encrypted format, steganography refers to confidential communication where the existence of the information, if any, is concealed. The JPEG image is used as the paper’s canopy. Koch’s snowflake fractal with a fourth iteration value is taken into account to provide a stego key. The text and fractal embedding within the host image of fractals have the distinctive property of neither changing the host image nor raising any red flags. The research is novel since it uses image steganography to make it more imperceptible. The host image maintains its mathematical behavior during embedding. Convolutional Neural Network (CNN) model is applied to enhance stego-image analysis and optimize embedding quality. The experimental results demonstrate that, in terms of capacity, robustness, and other statistical parameters, the proposed method performs superiority perceptually. The research is beneficial for hiding an image and sensitive data.