Image Vaccinator and Image Tamper Resilient and Lossless Auto-Recovery Using Invertible Neural Network

Aim: The aim of this endeavor attempts to identify tampering, provide lossless recovery, and improve picture data resilience against illegal adjustments. Materials and Methods: The current undertaking engages four distinct groups. Group 1, which includes the Convolutional Neural Network, specializes in learning pattern hierarchies within data, displaying efficiency in task management and Group 2 includes A Generative Adversarial Network c and Group 3 includes Recurrent Neural Networks (RNNs) store internal states to handle successive inputs and Group 4 includes Invertible Neural Network (INNs) provide bidirectional mappings at low additional cost, facilitating both forward and inverse operations. Results: The computed PSNR values demonstrate its dependability in keeping image authenticity online while maintaining high image quality throughout the procedure. PSNR of Slicing attack is 32.35 db. Conclusion: Using adversarial simulation and Invertible Neural Network technology, the Image Immunizer Middleware fortifies social network photos by introducing subtle perturbations and utilizing self-recovery passes for increased security.