Enhancing Privacy in Social Media Image Sharing Using Advanced Encryption Technique

As social media usage grows, protecting user privacy, especially in image sharing, is increasingly important.This paper explores enhancing privacy in social media image sharing using advanced encryption techniques based on chaotic neural networks.Chaotic neural networks, known for their complex and unpredictable behavior, offer strong encryption by transforming images into secure, unreadable formats.We discuss how these networks can effectively encrypt images during upload, store them securely, and ensure only authorized users can decrypt and view the images.This approach also includes using steganography to hide encrypted images within other files for added security.While chaotic neural networks provide robust encryption, they also introduce challenges like higher computational requirements and potential impacts on user experience.Optimizing these networks can mitigate such issues.Ensuring compliance with data protection laws like GDPR is crucial in this context.Future work may explore integrating quantumresistant encryption and AI-driven security enhancements.By leveraging chaotic neural networks, social media platforms can significantly improve the privacy and security of shared images, providing users with greater confidence in their privacy.