In this growing era, a massive amount of digital electronic health records (EHRs) are transferred through the open network. EHRs are at risk of a myriad of security threats, to overcome such threats, encryption is a reliable technique to secure data. This paper addresses an encryption algorithm based on integer wavelet transform (IWT) blended with deoxyribo nucleic acid (DNA) and chaos to secure the digital medical images. The proposed work comprises of two phases, i.e. a two-stage shuffling phase and diffusion phase. The first stage of shuffling starts with initial block confusion followed by row and column shuffling of pixels as the second stage. The pixels of the shuffled image are circularly shifted bitwise at the first stage of diffusion to enhance the security of the system against differential attack. The second stage of diffusion operation is based on DNA coding and DNA XOR operations. The experimental analyses have been carried out with 100 DICOM test images of 16-bit depth to evaluate the strength of the algorithm against statistical and differential attacks. By the results, the maximum entropy has been obtained an average of 15.79, NPCR of 99.99, UACI of 33.31, and larger keyspace of 10140, which infer that our technique overwhelms various other state-of-the-art techniques.

An efficient medical image encryption using hybrid DNA computing and chaos in transform domain

In order to enable interoperability between ontology-based systems, ontology matching techniques have been proposed. However, when the generated mappings lead to undesired logical consequences, their usefulness may be diminished. In this paper, we present an approach to detect and minimize the violations of the so-called conservativity principle where novel subsumption entailments between named concepts in one of the input ontologies are considered as unwanted. The practical applicability of the proposed approach is experimentally demonstrated on the datasets from the Ontology Alignment Evaluation Initiative.

/pdf/minimizing-conservativity-violations-in-ontology-alignments-48cvabyk02.pdf

Minimizing conservativity violations in ontology alignments: algorithms and evaluation

Reversible data hiding exploiting Huffman encoding with dual images for IoMT based healthcare

Recently, the use of industrial synthetic aperture radar (SAR) sensors for unmanned aerial vehicles (UAVs) has received more attention. Despite the recent growth in the use of SAR, the connection bandwidth and the low data rate communications among networked UAVs in an Internet of Things (IoT) environment is a challenge, specifically, for exchanging big data such as remote sensing videos. To this end, we propose a lossless data aggregation technique to reduce redundant information of industrial sensing and embed managerial and control data. The proposed method uses reversible watermarking through a dual-phase interpolation-based embedding with a greedy network of weights, which can be updated under an unsupervised statistical procedure. Our method is reversible with respect to enhanced embedding capacity for reliable wireless payload communications. The simulation results on the benchmarks of video synthetic aperture radar confirm the theoretical analysis and demonstrate that the proposed approach outperforms the past works.

Reliable Data Aggregation in Internet of ViSAR Vehicles Using Chained Dual-Phase Adaptive Interpolation and Data Embedding

Reversible data hiding (RDH) within images is the process of hiding secret data into a cover image in a way that the image can be completely recovered after extracting the embedded data. The performance of the RDH methods depends on making a trade of between the embedding capacity and the image quality. The aim of this paper is to improve RDH method within images using interpolation-based scheme. The proposed interpolation-based RDH (IRDH) scheme improves the embedding capacity of the state-of-the-art Lee and Huang's IRDH scheme with better image quality. The proposed scheme is choosing the existing enhanced neighbor mean interpolation (ENMI) and modified neighbor mean interpolation (MNMI) techniques to scale-up the original image before embedding the secret data. It is then hiding the sensitive bits via smartly benefitting from the principle idea of Lee and Huang's embedding technique. The experiments were conducted on eight standard images to evaluate the performance of the proposed scheme. The investigational results demonstrate that the proposed technique achieves the highest embedding capacity among the most striking similar works of Jung and Yoo's scheme, Lee and Huang's method, and Chang et al.'s approach, winning with attractive image quality.

Efficient Image Reversible Data Hiding Technique Based on Interpolation Optimization

Data Security Through Data Hiding in Images: A Review

Reversible data hiding (RDH) plays a key role in ensuring security of communications. Recent studies have revealed that RDH techniques based on interpolation are gaining popularity because of the ease of implementation and support for high embedding capacity. From recent literature, it is noted that the one-dimensional (1D) parabolic interpolation-based data hiding technique is suitable for high embedding capacity applications. This study aims to implement a high capacity RDH technique using a new two-dimensional (2D) parabolic interpolation and a novel embedding technique that is suitable for interpolation-based techniques. The results of this study showed that the proposed 2D parabolic interpolation maximized the utilization of the cover image pixels in up-sampling. The technique produced interpolated images of a higher quality compared to the 1D parabolic interpolation technique. Moreover, the proposed data hiding technique exploited the local redundancy and obtained the high embedding capacity with an appreciable image quality better than other state-of-the-art techniques. The results of this study support the view that the proposed parabolic interpolation has the potential to address security issues in high embedding capacity applications.

High capacity reversible data hiding using 2D parabolic interpolation

Comparative analysis of integer wavelet transforms in reversible data hiding using threshold based histogram modification

It is essential to maintain a proper balance between the embedding capacity, imperceptibility and robustness in image-based reversible data hiding (RDH) applications. Most of the spatial-domain RDH techniques focus more on embedding capacity and imperceptibility as compared to robustness, whereas transform-domain techniques concentrate mainly on imperceptibility and robustness. Hence, there is a need to implement a technique which maintains a proper trade-off among all the three parameters. A scheme that uses a combination of spatial- and transform-domain (hybrid) techniques is proposed here. A threshold-based difference histogram modification (TDHM) is used as a building block for data embedding and extraction. In the proposed technique, the cover image is systematically modified using spatial-domain rhombus prediction-based prediction error histogram modification and integer Haar wavelet transform (IHWT)-based TDHM (IHWT-TDHM) techniques. The experimental results show that the stated methodology accomplishes a higher embedding capacity while maintaining good imperceptibility and robustness compared to that of the direct spatial or transform RDH techniques.

A New Image-Based Hybrid Reversible Data Hiding Model Using IHWT and RP-PEHM for Secured Data Communication

Reversible Data Hiding (RDH) using images is currently highly focused research area in information security. RDH techniques are broadly classified into two types viz., spatial and transform domain. From the literature survey it is noted that, transform domain techniques are used to produce imperceptible and undetectable stego images. Hence, in this study we have proposed two integer wavelet transforms viz., 5/3 and 9/7 based RDH techniques. Here Prediction Error Expansion (PEE) has been used as a data hiding technique. To analyse the performance of the proposed transforms in PEE, standard Haar transform also used. Apart from that, state of the art RDH techniques are used for comparison purpose. The experimental results indicate that, the proposed transforms have outperformed the state-of-the-art techniques with respect both visual quality and embedding capacity.

Ahmad Shaik

Papers

Data Security Through Data Hiding in Images: A Review

High capacity reversible data hiding using 2D parabolic interpolation

Comparative analysis of integer wavelet transforms in reversible data hiding using threshold based histogram modification

A New Image-Based Hybrid Reversible Data Hiding Model Using IHWT and RP-PEHM for Secured Data Communication

Reversible Data Hiding Based on Integer Wavelet Transforms and Prediction Error Expansion