A Survey on Reversible Image Data Hiding Using the Hierarchical Block Embedding Technique

The use of graphics for data concealment has significantly advanced the fields of secure communication and identity verification. Reversible data hiding (RDH) involves hiding data within host media, such as images, while allowing for the recovery of the original cover. Various RDH approaches have been developed, including difference expansion, interpolation techniques, prediction, and histogram modification. However, these methods were primarily applied to plain photos. This study introduces a novel reversible image transformation technique called Block Hierarchical Substitution (BHS). BHS enhances the quality of encrypted images and enables lossless restoration of the secret image with a low Peak Signal-to-Noise Ratio (PSNR). The cover image is divided into non-overlapping blocks, and the pixel values within each block are encrypted using the modulo function. This ensures that the linear prediction difference in the block remains consistent before and after encryption, enabling independent data extraction without picture decryption. In order to address the challenges associated with secure multimedia data processing, such as data encryption during transmission and storage, this survey investigates the specific issues related to reversible data hiding in encrypted images (RDHEI). Our proposed solution aims to enhance security (low Mean Squared Error) and improve the PSNR value by applying the method to encrypted images

A Multistage High Capacity Reversible Data Hiding Technique Without Overhead Communication

Reversible Data Hiding(RDH) has been extensively investigated, recently, due to its numerous applications in the field of defence, medical, law enforcement and image authentication. However, most of RDH techniques suffer from low secret data hiding capacity and communication overhead. For this, multistage high-capacity reversible data hiding technique without overhead is proposed in this manuscript. Proposed reversible data hiding approach exploits histogram peaks for embedding the secret data along with overhead bits both in plain and encrypted domain. First, marked image is obtained by embedding secret data in the plain domain which is further processed using affine cipher maintaining correlation among the pixels. In second stage, overhead bits are embedded in the encrypted marked image. High embedding capacity is achieved through exploiting histogram peak for embedding multiple bits of secret data. Proposed approach is experimentally validated on different datasets and results are compared with the state-of-the-art techniques over different images

The Realizations of Steganography in Encrypted Domain

With the popularization and application of privacy protection technologies in cloud service and social network, ciphertext has been gradually becoming a common platform for public to exchange data. Under the cover of such a plat-form, we propose steganography in encrypted domain (SIED) in this paper to re-alize a novel method to realize secret communication Based on Simmons' model of prisoners' problems, we discuss the application scenarios of SIED. According to the different accesses to the encryption key and decryption key for secret mes-sage sender or receiver, the application modes of SIED are classified into four modes. To analyze the security requirments of SIED, four levels of steganalysis attacks are introduced based on the prior knowledge about the steganography system that the attacker is assumed to obtain in advance. Four levels of security standards of SIED are defined correspondingly. Based on the existing reversible data hiding techniques, we give four schemes of SIED as practical instances with different security levels. By analyzing the embedding and extraction characteris-tics of each instance, their SIED modes, application frameworks and security lev-els are discussed in detail

Privacy-preserving information hiding and its applications

The phenomenal advances in cloud computing technology have raised concerns about data privacy. Aided by the modern cryptographic techniques such as homomorphic encryption, it has become possible to carry out computations in the encrypted domain and process data without compromising information privacy. In this thesis, we study various classes of privacy-preserving information hiding schemes and their real-world applications for cyber security, cloud computing, Internet of things, etc. Data breach is recognised as one of the most dreadful cyber security threats in which private data is copied, transmitted, viewed, stolen or used by unauthorised parties. Although encryption can obfuscate private information against unauthorised viewing, it may not stop data from illegitimate exportation. Privacy-preserving Information hiding can serve as a potential solution to this issue in such a manner that a permission code is embedded into the encrypted data and can be detected when transmissions occur. Digital watermarking is a technique that has been used for a wide range of intriguing applications such as data authentication and ownership identification. However, some of the algorithms are proprietary intellectual properties and thus the availability to the general public is rather limited. A possible solution is to outsource the task of watermarking to an authorised cloud service provider, that has legitimate right to execute the algorithms as well as high computational capacity. Privacypreserving Information hiding is well suited to this scenario since it is operated in the encrypted domain and hence prevents private data from being collected by the cloud. Internet of things is a promising technology to healthcare industry. A common framework consists of wearable equipments for monitoring the health status of an individual, a local gateway device for aggregating the data, and a cloud server for storing and analysing the data. However, there are risks that an adversary may attempt to eavesdrop the wireless communication, attack the gateway device or even access to the cloud server. Hence, it is desirable to produce and encrypt the data simultaneously and incorporate secret sharing schemes to realise access control. Privacy-preserving secret sharing is a novel research for fulfilling this function. In summary, this thesis presents novel schemes and algorithms, including: • two privacy-preserving reversible information hiding schemes based upon symmetric cryptography using arithmetic of quadratic residues and lexicographic permutations, respectively. • two privacy-preserving reversible information hiding schemes based upon asymmetric cryptography using multiplicative and additive privacy homomorphisms, respectively. • four predictive models for assisting the removal of distortions inflicted by information hiding based respectively upon projection theorem, image gradient, total variation denoising, and Bayesian inference. • three privacy-preserving secret sharing algorithms with different levels of generality