Quantum Adaptive Pixel Shuffling and Blockchain Integrated Steganographic Encryption for Securing Data in the Quantum Era

In today's digital era secure data transmission faces critical challenges because quantum computing continues to increase threats against existing systems. Traditional encryption algorithmic program and steganographic methods establish increasing vulnerability to quantum attacks as considerably as sophisticated steganalysis techniques. This research tender a root through Quantum Adaptive Pixel Shuffling and Blockchain Integrated Steganographic Encryption Framework to harness these challenges. The system apply Quantum-Inspired Reinforcement Learning (QIRL) to shuffle pixels dynamically and increase resistance against steganalysis while conserve irregular data embedding. The system uses a Post-Quantum Lightweight Encryption algorithm which relies on lattice cryptanalytics to guard data point against quantum decryption proficiency. The system uses Blockchain-Assisted Hash Least Significant Bit (BHLSB) Secret Writing to enable decentralised substantiation unconscious process that protect datum against unauthorized change while defend data point integrity. Standard bench mark prototype were used to quiz the proposed fabric which reach a PSNR of 61. 67 dB and a SSIM of 0. 9999 at low implant pace thus evidence excellent conservation of image quality. The system point decreased MSE note value and stiff resistance to noise, compaction and fiddle when equate to traditional methods. Blockchain verification sustain over 95% success rate to support data integrity. The PQLE encryption method showed huge resistance to quantum decipherment onslaught through exponential metier. The fresh fabric overcomes current defect to deliver a dependable, scalable solution subject of protect data point for next applications. Through the development of a new adaptive data encryption and steganography model this study prepare a substantive contribution to cybersecurity research by offering quantum resistance.