Reversible Data Hiding in Encrypted Images Based on Hybrid Chaotic Logistic Map and Tent Map to Protect Privacy of User in Cloud

Abstract

Reversible data hiding in encrypted images (RDHEI) serves a dual purpose in today's environment, where cloud storage and privacy protection are becoming increasingly crucial by acting as both a privacy safeguard and a means of transferring private information. This paper provides a Hamming Code according to our proposed prediction and detection methods. The image is encrypted first by the content owner, who employs a hybrid chaotic logistic and tent map function.  A robust cryptosystem based on a 3D chaotic map for image encryption in secure cloud services. The proposed encryption method depends on a mix of 3D Tent and 3D Logistic chaotic maps. With this map, a nonlinear ciphering process is implemented for pixel value diffusion and position permutation. A chaotic sequence is used to generate the user-defined key. The data hider will then include the data through a technique known as histogram modification. We use histogram shifting. Based on the code, the user could either obtain the hidden data by image encrypting that contains protected private data or decode and recreate the secured personal mage. We get an average entropy of encrypted image 7.99, NPCR of 99.6% and UACI of 33.5%. Compared with previous studies, a novel method we created simplifies the scheme significantly while achieving better data processing performance loss and hiding capacity.