Reversible data hiding and authentication scheme for encrypted image based on prediction error compression.

Area of Science:

• Computer Science
• Information Security
• Digital Forensics

Background:

• Existing reversible data hiding schemes for encrypted images often fail to guarantee image content integrity.
• Reversible recovery of cover images is possible, but content authentication remains a challenge.

Purpose of the Study:

• To propose a novel reversible data hiding and authentication scheme for encrypted images.
• To ensure reversible recovery of cover images and authentication of both cover image content and secret data.
• To enhance security, embedding capacity, and data integrity in encrypted image steganography.

Main Methods:

• Utilizes a new predictor, ISGAP (Image Structure Guided Adaptive Prediction), for more accurate predictions and smaller prediction errors.
• Employs adaptive Huffman coding to compress prediction errors, increasing the embedding space for plaintext authentication information.
• Embeds secret data and ciphertext authentication information into the encrypted image by the data hider.
• Receiver performs ciphertext authentication before cover recovery and plaintext authentication using distinct keys.

Main Results:

• The proposed scheme demonstrates higher embedding capacity compared to existing methods.
• Effectively implements image content authentication.
• Ensures high security and reversible recovery of the original image and secret data.
• Experimental validation conducted on 100 images from BOSSbase and BOWS-2 datasets.

Conclusions:

• The developed scheme successfully integrates reversible data hiding with robust authentication for encrypted images.
• It addresses the limitations of previous methods by guaranteeing content integrity alongside reversible recovery.
• The scheme offers a significant advancement in secure and reliable steganography for digital images.