Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

Reversible Data Hiding scheme using modified Histogram Shifting in Encrypted Images for Bio-medical images

Existing Least Significant Bit (LSB) steganography system is less robust and the stego-images can be corrupted easily by attackers. To overcome these problems Reversible data hiding (RDH) techniques are used. RDH is an efficient way of embedding confidential message into a cover image. Histogram expansion and histogram shifting are effective techniques in reversible data hiding. The embedded message and cover images can be extracted without any distortion. The proposed system focuses on implementation of RDH techniques for hiding data in encrypted bio-medical images without any loss. In the proposed techniques the bio-medical data are embedded into cover images by reversible data hiding technique. Histogram expansion and histogram shifting have been used to extract cover image and bio- medical data. Each pixel is encrypted by public key of Paillier cryptosystem algorithm. The homomorphic multiplication is used to expand the histogram of the image in encrypted domain. The histogram shifting is done based on the homomorphic addition and adjacent pixel difference in the encrypted domain. The message is embedded into the host image pixel difference. On receiving encrypted image with additional data, the receiver using his private key performs decryption. As a result, due to histogram expansion and histogram shifting embedded message and the host image can be recovered perfectly. The embedding rate is increased in host image than in existing scheme due to adjacency pixel difference

Framework for reversible data hiding using cost-effective encoding system for video steganography

Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data

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

IMG-GUARD: Watermark Based Approach for Image Privacy in OSN Framework

A social networking service (also social networking site, SNS or social media) is an online platform that is used by people to build social networks or social relations with another persons who are share their own details or career interests, activities, backgrounds or real-life connections. Social networking sites are varied and they incorporate a range of new information and various tools such as availability personal computers, mobile devices such as tablet computers and smart phones, digital photo/video/sharing and "web logging" diary entries online (blogging). While Online Social Networks (OSNs) enable users to share photos easily, they also expose users to several privacy threats from both the OSNs and external entities. The current privacy controls on social networks are far from adequate, resulting in inappropriate flows of information when users fail to understand their privacy settings or OSNs fail to implement policies correctly. Social networks may be complicated because of privacy expectations when they reserve the right to analyze uploaded photos using automated watermarking technique. A user who uploads digital data such as image to their home page may wish to share it with only mutual friends, which OSNs partially satisfy with privacy settings. In this paper, we concentrate to solve the privacy violation problem occurred when images are published on the online social networks without the permission. According to such images are always shared after uploading process. Therefore, the digital image watermarking based on DWT co-efficient. Watermark bits are embedded in uploaded images. Watermarked images are shared in user homages can be difficult to misuse by other persons

Comparative Analysis of Image Enhancement Quality Based on Domains

First method is spatial domain and the effective of four diverse image spatial techniques (histogram equalization, adaptive histogram, histogram matching, and unsharp masking) produce sharpening and smoothening of image. Secondly, frequency domain technique and the effective of three diverse image spatial techniques (bilateral, homo-morphic and trilateral filter) were examined to achieve low noise image. Finally, SVD,QR,SLANT and HADAMARD was examined whichincreased human visual. For the above techniques, different quality parameters are evaluated. From the above evaluation, the proposed method identifies the best method among the three domains

HIGH CAPACITY AND OPTIMIZED IMAGE STEGANOGRAPHY TECHNIQUE BASED ON ANT COLONY OPTIMIZATION ALGORITHM

The tremendous development of digital technology, it is mandatory to address the security while transmitting information over network in a way that observer couldn’t depict it. Measures to be taken to provide the security by establishing hidden communication using steganography principle which is help to camouflage the secret information in some carrier file such as text, image, audio and video. In this era of hidden data communication, image becoming an effective tool on account of their frequency, capability and accuracy. Image steganography uses an image as a carrier medium to hide the secret data. The main motive of this article is that the uses the combination of frequency domain and optimization method inorder to increasing in robustness. In this article, Integer Wavelet transform is performed into the host image and coefficients have been transformed. ACO optimization algorithm is used to find the optimal coefficients where to hide the data. Furthermore, sample images and information having been demonstrated which proved the increased robustness as well as high level of data embedding capacity

Diff-Privacy: Diffusion-based Face Privacy Protection

Privacy protection has become a top priority as the proliferation of AI techniques has led to widespread collection and misuse of personal data. Anonymization and visual identity information hiding are two important facial privacy protection tasks that aim to remove identification characteristics from facial images at the human perception level. However, they have a significant difference in that the former aims to prevent the machine from recognizing correctly, while the latter needs to ensure the accuracy of machine recognition. Therefore, it is difficult to train a model to complete these two tasks simultaneously. In this paper, we unify the task of anonymization and visual identity information hiding and propose a novel face privacy protection method based on diffusion models, dubbed Diff-Privacy. Specifically, we train our proposed multi-scale image inversion module (MSI) to obtain a set of SDM format conditional embeddings of the original image. Based on the conditional embeddings, we design corresponding embedding scheduling strategies and construct different energy functions during the denoising process to achieve anonymization and visual identity information hiding. Extensive experiments have been conducted to validate the effectiveness of our proposed framework in protecting facial privacy.Comment: 17page

Multimedia security and privacy protection in the internet of things: research developments and challenges

With the rapid growth of the internet of things (IoT), huge amounts of multimedia data are being generated from and/or exchanged through various IoT devices, systems and applications. The security and privacy of multimedia data have, however, emerged as key challenges that have the potential to impact the successful deployment of IoT devices in some data-sensitive applications. In this paper, we conduct a comprehensive survey on multimedia data security and privacy protection in the IoT. First, we classify multimedia data into different types and security levels according to application areas. Then, we analyse and discuss the existing multimedia data protection schemes in the IoT, including traditional techniques (e.g., cryptography and watermarking) and emerging technologies (e.g., blockchain and federated learning). Based on the detailed analysis on the research development of IoT-related multimedia security and privacy protection, we point out some open challenges and provide future research directions, aiming to advance the study in the relevant fields and assist researchers in gaining a deeper understanding of the state of the art on multimedia data protection in the IoT