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

APPLICATION OF GENETIC ALGORITHM FOR IMAGE TRANSFER

For images transfer, different embedding system exist which works by creating a mosaic image from the source image and recovery from the target image using some sort of algorithm. In current study, a method is proposed using the genetic algorithm for recovery of image from the source image. The algorithm utilized is genetic algorithm which is a search method along with another additional technique for obtaining higher robustness and security. The proposed methodology works by dividing the source image into smaller parts which are fitted into target image using the lossless compression. The mosaic image is recovered at retrieving side by the permutation array which is recovered and mapped using the pre-select key

Visual Privacy Protection Methods: A Survey

Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambient-assisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual’s privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users’ acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people’s privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.This work has been partially supported by the Spanish Ministry of Science and Innovation under project “Sistema de visión para la monitorización de la actividad de la vida diaria en el hogar” (TIN2010-20510-C04-02) and by the European Commission under project “caring4U - A study on people activity in private spaces: towards a multisensor network that meets privacy requirements” (PIEF-GA-2010-274649). José Ramón Padilla López and Alexandros Andre Chaaraoui acknowledge financial support by the Conselleria d'Educació, Formació i Ocupació of the Generalitat Valenciana (fellowship ACIF/2012/064 and ACIF/2011/160 respectively)

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

An efficient data masking for securing medical data using DNA encoding and chaotic system

Data security is utmost important for ubiquitous computing of medical/diagnostic data or images. Along with must consider preserving privacy of patients. Recently, deoxyribose nucleic acid (DNA) sequences and chaotic sequence are jointly used for building efficient data masking model. However, the state-of-art model are not robust against noise and cropping attack (CA). Since in existing model most digits of each pixel are not altered. This work present efficient data masking (EDM) method using chaos and DNA based encryption method for securing health care data. For overcoming research challenges effective bit scrambling method is required. Firstly, this work present an efficient bit scrambling using logistic sine map and pseudorandom sequence using chaotic system. Then, DNA substitution is performed among them to resist against differential attack (DA), statistical attack (SA) and CA. Experiment are conducted on standard considering diverse images. The outcome achieved shows proposed model efficient when compared to existing models

A review of compressive sensing in information security field

The applications of compressive sensing (CS) in the fi eld of information security have captured a great deal of researchers\u27 attention in the past decade. To supply guidance for researchers from a comprehensive perspective, this paper, for the fi rst time, reviews CS in information security field from two aspects: theoretical security and application security. Moreover, the CS applied in image cipher is one of the most widespread applications, as its characteristics of dimensional reduction and random projection can be utilized and integrated into image cryptosystems, which can achieve simultaneous compression and encryption of an image or multiple images. With respect to this application, the basic framework designs and the corresponding analyses are investigated. Speci fically, the investigation proceeds from three aspects, namely, image ciphers based on chaos and CS, image ciphers based on optics and CS, and image ciphers based on chaos, optics, and CS. A total of six frameworks are put forward. Meanwhile, their analyses in terms of security, advantages, disadvantages, and so on are presented. At last, we attempt to indicate some other possible application research topics in future

Data security in the Industrial Internet of Things (IIoT) through a triple-image encryption framework leveraging 3-D NEAT, 1DCJ, and 4DHCFO techniques

In the Industrial Internet of Things (IIoT) era, protecting vast data volumes, including sensitive information, poses a significant security challenge. To address this issue, this research proposes a novel triple-image encryption method tailored for IIoT applications. Unlike conventional algorithms processing a single grayscale image to produce a corresponding single ciphertext, the proposed approach generates a single color encrypted image corresponding to three grayscale input images. This complexity adds an extra layer of challenge for unauthorized individuals attempting to recover plaintext data. Leveraging the 3-D non-equilateral Arnold transform (NEAT), extended one-dimensional chaotic jumping (1DCJ), and a four-dimensional hyperchaotic Chen map of fractional order (4DHCFO), the proposed method begins by processing three grayscale images—R gray, G gray, and B gray—with a 3-D NEAT to scramble their pixel positions. Employing three distinct scrambling operations, multilayer permutation, multiround permutation, and diagonal permutation, enhances scrambling complexity. Subsequently, binary bit planes are extracted and subjected to bit-level scrambling via 1DCJ. Further, a 4DHCFO generates a 16 × 16 substitution box for diffusing scrambled bit planes using XOR operations. Experimental analyses encompassing entropy, correlation, energy, histogram, key sensitivity, key space, NPCR, and UACI reveal the efficacy of the proposed scheme. The scheme demonstrates significant statistical values (entropy: 7.9999, correlation: 0.0001, NPCR: 33.96, UACI: 96.79) and operates efficiently with a computational time of 0.002 for encrypting triple grayscale images simultaneously which shows its suitability for real-time applications

A Novel Approach for Enhancement of Blowfish Algorithm by using DES, DCT Methods for Providing, Strong Encryption and Decryption Capabilities

Data safety has evolved into a critical requirement and a duty in modern life. Most of our systems are designed in such a way that it can get hacked, putting our private information at danger. As a result, for numerous safety motives, we utilize various approaches to save as much as possible on this data, regardless of its varied formats, words, photographs, videos, and so on. The data storage capacity of mobile devices is restricted owing to insufficient data storage and processing. In order to develop a safe MCC environment, security concerns must be studied and analysed. This study compares the most widely used symmetric key encryption algorithms, including DES (Data Encryption Standard), Blowfish, TDES (Triple Data Encryption Standard), PRESENT, and KLEIN. The assessment of algorithms is based on attacks, key size, and block size, with the best outcomes in their field

Privacy-preserving inpainting for outsourced image

In this article, a framework of privacy-preserving inpainting for outsourced image and an encrypted-image inpainting scheme are proposed. Different with conventional image inpainting in plaintext domain, there are two entities, that is, content owner and image restorer, in our framework. Content owner first encrypts his or her damaged image for privacy protection and outsources the encrypted, damaged image to image restorer, who may be a cloud server with powerful computation capability. Image restorer performs inpainting in encrypted domain and sends the inpainted and encrypted image back to content owner or authorized receiver, who can acquire final inpainted result in plaintext domain through decryption. In our encrypted-image inpainting scheme, with the assist of Johnson–Lindenstrauss transform that can preserve Euclidean distance between two vectors before and after encryption, the best-matching block with the smallest distance to current block can be found and utilized for patch filling in Paillier-encrypted image. To eliminate mosaic effect after decryption, weighted mean filtering in encrypted domain is conducted with Paillier homomorphic properties. Experimental results show that our privacy-preserving inpainting framework can be effectively applied in secure cloud computing, and the proposed encrypted-image inpainting scheme achieves comparable visual quality of inpainted results with some typical inpainting schemes in plaintext domain