Image Information Security Protection in the Big Data Era Based on Reversible Data Hiding in Encrypted Images

Abstract

Massive image sharing and cloud-based storage in big data environments have significantly increased the risks of privacy leakage, unauthorized tampering, and insecure transmission. To address these issues, a reversible data hiding in encrypted images (RDHEI) framework integrating reserved room before encryption (RRBE) and vacating room after encryption (VRAE) is proposed for secure image information protection. The method combines high-bit plane prediction compression, key-controlled image encryption, and ciphertext-domain adaptive embedding to simultaneously achieve high-capacity data hiding, strict permission separation, and lossless image recovery. In addition, an error reverse reduction mechanism is introduced to suppress pixel distortion and improve recovery stability. Experimental evaluation is conducted on the UCID public image dataset containing 1338 uncompressed color images with rich texture and structural characteristics, including natural scenes, urban buildings, portraits, vehicles, plants, animals, and indoor environments. Experimental results on the UCID dataset demonstrate that the proposed method achieves an embedding rate of 0.99 bpp, a payload capacity of 524000 bits, Peak Signal-to-Noise Ratio (PSNR) of 52.14 dB, and Structural Similarity Index Measure (SSIM) of 0.994. Meanwhile, the bit error rate is reduced to 0.028, the information entropy reaches 7.999, and the Number of Pixels Change Rate (NPCR) reaches 99.37%, indicating strong encryption randomness and resistance to differential attacks. Compared with Convolutional Neural Network-based Reversible Data Hiding (CNN-RDH) and Generative Adversarial Network-based Reversible Data Hiding (GAN-RDH) methods, the proposed framework achieves superior performance in embedding efficiency, recovery accuracy, visual quality, and computational efficiency. The proposed RDHEI framework provides an effective and scalable solution for secure image storage, privacy-preserving transmission, and encrypted multimedia sharing in large-scale big data applications.