An enhanced reversible patient data hiding algorithm for E-healthcare

doi:10.1016/j.bspc.2020.102276

Biomedical Signal Processing and Control

Volume 64, February 2021, 102276

https://doi.org/10.1016/j.bspc.2020.102276 Get rights and content

Highlights

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Average pixel repetition (APR) method is used for interpolation to avoid underflow and overflow problem during data embedding in scaled-up image.
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The EPI is embedded in $b a s e_{k}$ numeral framework to improve the embedding capacity.
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Fragile watermark is used for content authentication at the receiver end.

Abstract

The feasibility of future developments in computing technologies strongly relies on the existence of key technologies and their deployments. One of the areas where they are being deployed is telemedicine, it requires communication of patient report to a specialized doctor in a real time scenario. Therefore, any harm to patient medical data can lead to a faulty diagnosis that can be lethal for the patient. To ensure safe and secure communication in E-healthcare framework, a high capacity reversible data hiding algorithm in the encrypted domain has been proposed in this paper. The proposed algorithm gives a higher embedding rate by embedding $n$ binary bits of patient data in $b a s e_{k}$ numeral framework at every pixel of the cover image without any occurrence of underflow and overflow problem. In addition to electronic patient information (EPI), a fragile watermark has been embedded for observing any tamper to the patient data during transmission phase. The experimental study reveals that for all types of test images, proposed method has an embedding rate nearly twice larger than the compared methods, precisely recover EPI with a PSNR value of $\infty$ dB between the cover image and reconstructed image successfully.

Introduction

Electronic healthcare (E-healthcare) systems are currently being integrated with conventional health care systems to acquire benefits of current-day technological advancements [1]. The current E-healthcare system is doing telediagnosis of a patient, for this purpose, it requires medical reports of the patient including all image and text-based reports to share among its remote centers [2]. Though E-healthcare systems bring the best medical facilities at your doorsteps, but during implementation process experiences some challenges also. One of the fundamental concerns to be addressed for the implementation of E-healthcare system is security, authentication and copyright protection of the patient data respectively [3]. Data hiding is the most robust tool that can address the above-mentioned issues. Various data hiding techniques are applied to protect data integrity and through these techniques, one can ensure data reliability. Sometimes, during the data hiding process, receiver is not able to reconstructed cover image successfully while in few applications, for example, medical, military, and law crime scene investigation, loss of cover image is not permitted. In these cases, an extraordinary sort of data hiding strategy called reversible or lossless data hiding is utilized. Reversible data hiding meant to embed the secret message in cover image in such a way that at receiver end, secret message as well as original cover image is recovered successfully. Encryption is the most promising solution to maintain confidentiality and privacy of data. The integration of encryption and RDH technologies plays an important role in privacy protection. As a result, reversible data hiding (RDH) in encrypted image (RDH-EI) has attracted a great attention from the research community.

Section snippets

Literature review

There is a lot of research done in reversible data hiding domain; some are illustrated as follows — Firstly, the idea of hiding information from attackers was presented by Shi [4]. Afterward, difference expansion based reversible data hiding technique was proposed by Tian [5], where a single bit was embedded between two close-by pixels through difference computation. Ni et al. [6] had given a method where a secret message is embedded at the histogram’s peak point of cover image. Afterward, Bo

Preliminaries

Firstly, proposed work interpolated cover image to implement reversible data hiding algorithm without any underflow and overflow problem. Basic concept of interpolation process is covered in this section to make readers familiar with it.

Proposed algorithm

Now a days, patient data privacy and security is one of the most significant challenge for telemedicine applications. Consider a scenario where patient’s data is sent to doctor/surgeon; hacker may observed the healthcare information. Later, an attacker may float this information on social sites and this action may put tremendous threats to the patient’s confidentiality. The appropriate encryption and authentication schemes can be useful to prevent these type of attacks. To ensure secure and

Results and discussion

The experimental study has been carried out using MATLAB R2017a platform for different $512 \times 512$ test images obtained from open-source image database (USC-SIPI) whereas medical images obtained from the database of The Cancer Imaging Archive (TCIA) as shown in Fig. 2 respectively. Here, we examine the performance of the proposed method which is evaluated using metrics like Bit Error Rate (BER) and Embedding Rate (bpp) respectively. The embedding rate indicated by R is described as payload of

Conclusion

Data hiding applications in the E-healthcare framework have an extreme indulgence with reversibility, high payload and content authentication. To recover the original medical image at receiver end for diagnosis and transfer of high payload, an enhanced reversible data hiding technique in encrypted domain has been proposed in this paper. The proposed algorithm gives higher embedding rate by embedding $n$ binary bits of patient data in $b a s e_{k}$ numeral framework at every pixel of the cover image

Declaration of Competing Interest

One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.bspc.2020.102276.

References (31)

YangZhe et al.
An iot-cloud based wearable ecg monitoring system for smart healthcare
J. Med. Syst.
(2016)
WuXiaotian et al.
High-capacity reversible data hiding in encrypted images by prediction error
Signal Process.
(2014)
WuXiaotian et al.
Reversible data hiding for encrypted signals by homomorphic encryption and signal energy transfer
J. Vis. Commun. Image Represent.
(2016)
LuTzu-Chuen et al.
Dual-image-based reversible data hiding method using center folding strategy
Signal Process.
(2015)
ShiuHung-Jr et al.
Preserving privacy of online digital physiological signals using blind and reversible steganography
Comput. Methods Programs Biomed.
(2017)
ParahShabir A. et al.
Hiding clinical information in medical images: a new high capacity and reversible data hiding technique
J. Biomed. Inform.
(2017)
BhaleraoSiddharth et al.
A reversible and multipurpose ecg data hiding technique for telemedicine applications
Pattern Recognit. Lett.
(2019)
CoventryLynne et al.
Cybersecurity in healthcare: a narrative review of trends, threats and ways forward
Maturitas
(2018)
IeracitanoCosimo et al.
A novel statistical analysis and autoencoder driven intelligent intrusion detection approach
Neurocomputing
(2020)
ShimizuKoichi
Telemedicine by mobile communication
IEEE Eng. Med. Biol. Mag.
(1999)

PuteauxPauline et al.

An efficient msb prediction-based method for high-capacity reversible data hiding in encrypted images

IEEE Trans. Inf. Forensics Secur.

(2018)

ShiYun Q.

Reversible data hiding

TianJun

Reversible data embedding using a difference expansion

IEEE Trans. Circuits Syst. Video Technol.

(2003)

NiZhicheng et al.

Reversible data hiding

IEEE Trans. Circuits Syst. Video Technol.

(2006)

XiaoB. et al.

Reversible data hiding using histogram shifting in small blocks

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Reversible data hiding in encrypted image with secure multi-party for telemedicine applications
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Privacy protection of electronic patient information (EPI) is a crucial concern in the telemedicine applications, especially when it comes to communication between patients and doctors. In this paper, we propose a high-capacity reversible data hiding (RDH) algorithm combined with secure multi-party computation for telemedicine applications. The pixel values within a 3 × 3-size image block are divided into embedded pixels (EPs) and sampled pixels (SPs), secret data is embedded into the prediction errors of EPs and SPs in two stages. In the first stage, two edge servers predict EPs using the four SPs in the block to obtain the prediction error of EPs. The secret data is embedded into EPs through addition operation and histogram shift method. In the second stage, the prediction error of SPs is calculated as the difference between EPs and SPs, and the embedding of secret data follows the same method as used in the first stage. The experimental results demonstrate that the proposed algorithm achieves a higher embedding rate compared to classical and state-of-the-art algorithms, with an average embedding rate of 0.47bpp on the UCID dataset. Furthermore, the proposed algorithm exhibits robustness against existing attacks.
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Image authentication techniques are crucial for a multitude of multimedia applications. When images are transmitted through non-secure channels like the internet, they are vulnerable to unauthorized alterations and manipulations. Therefore, it is essential in sensitive fields, like the medical industry, to employ image authentication techniques to guarantee the integrity and authenticity of transmitted images. In this paper, to address these security issues and to ensure the authenticity of medical images, we present a reversible fragile watermarking model where the watermark is first generated from the cover image using DCT and then encrypted by the Fibonacci Q-matrix technique, enhancing the model’s security. Subsequently, DFT is performed on the host image and the obtained sub-band is segmented into 2 × 2 blocks, the watermark is then embedded within the frequency coefficients using a new embedding technique. Experimental results indicates that the presented model produces a great watermarked image quality, with a PSNR superior to 117 dB, while maintaining an acceptable embedding capacity of 0.25 BPP and high sensitivity to various attacks, as it was tested against 16 different attacks and could detect tampering in all of them. Furthermore, the presented scheme offers nearly perfect reversibility with a PSNR of 324 dB, which is very useful in the medical field where we need images with as little distortion as possible.
ECG signals-based security and steganography approaches in WBANs: A comprehensive survey and taxonomy
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Wireless Body Area Networks (WBANs) are integral components of e-healthcare systems, responsible for monitoring patients' physiological states through intelligent implantable or wearable sensor nodes. These nodes collect medical data, which is then transmitted to remote healthcare facilities for thorough evaluation. Securing medical data within WBANs is paramount due to its central role in preserving patient privacy and confidentiality. Notably, Electrocardiogram (ECG) signals have recently gained prominence as pivotal elements within diverse security frameworks. Incorporating ECG signals strategically enhances the security and reliability of WBANs and broader e-healthcare systems, instilling greater trustworthiness. This survey article provides an in-depth exploration of contemporary ECG-based security schemes, adding to the scholarly discourse. The imperative to categorize these security paradigms revolves around their use of ECG signals. This categorization identifies three key domains: the first involves schemes that utilize ECG signals for cryptographic operations, encompassing key generation, agreement, management, and authentication. The second category employs steganography-based techniques, using ECG signals to conceal patients' sensitive medical data. The third category focuses on enhancing ECG signal security during data transmission. Each category is meticulously elaborated, detailing architectural foundations, notable contributions, and intrinsic security services. Furthermore, each section presents a comprehensive overview of the attributes characterizing ECG-based security frameworks. This includes insights into employed datasets, simulation environments, evaluation metrics, and inherent advantages and limitations. Expanding on this, a thorough analysis of distinctive attributes underpinning these security frameworks concludes by shedding light on potential directions for future research.
Separable and reversible data hiding scheme for medical images using modified Logistic and interpolation
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The interpolation technique (IT) is a fundamental tool for image processing and is commonly utilized. Various IT-based reversible data hiding (RDH) schemes for encrypted medical images have been proposed in recent years. However, these schemes have encountered issues such as simplistic encryption, low embedding rate, or incomplete separation. A high-capacity IT-based separable RDH scheme for medical images is proposed to address these issues. First, the original Logistic map is modified by adding extra parameters to increase the complexity of the key. Additionally, an encryption method via bit reorganization and diffusion is presented to encrypt the original image. Second, an improved interpolation method based on the neighbor pixel mean is proposed to interpolate the encrypted (ciphertext) image to generate a cover (interpolated) image for embedding the data. Finally, a new data embedding method is developed using the modulo-operation congruence theorem. Experimental results showed that the modified Logistic map exhibits excellent chaotic characteristics, the metrics of the proposed encryption method are close to the theoretical values, and the proposed data hiding method acquires high embedding capacity and image quality. Furthermore, the proposed scheme is a fully reversible and separable technique that achieves superior performance in comparison to various IT-based encrypted RDH schemes.
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In this paper, we propose a data hiding technique that helps the receiver to extract the secret data and recover the original image. The receiver first creates a pair of keys using Paillier cryptosystem and shares public key with sender. The sender enlarges cover image of size M × N to (2M − 1) × (2N − 1) by inserting one row (column) between two rows (columns), and then divides it into 3 × 3 blocks such that two boundary blocks have a row or a column in common, and two interior blocks have one row and one column in common. The block’s corner pixels, called as seed pixels, belong cover image and others, called as non-seed pixels, are initialized as 1 that are updated while embedding secret data in seed pixels. The block’s central pixels hide a secret bit using the parity and seed pixels are processed clockwise to hide two secret bits in each using separate procedures for even and odd pixels. The seed’s next pixel is multiplied by a fixed number that helps receiver to determine how it was processed at sender side. All pixels are encrypted using Paillier public key, giving a stegoimage, that is transmitted to the receiver. The receiver decrypts the stegoimage using Paillier private key, extracts the secret data and cover image by performing the data extraction process. The embedding rate of proposed method is 2.24 bits per pixel, which is 12 %, 16 %, 89 %, 83 %, 114 %, better than the Bhardwaj, Wang et al., Chen-Chang, Chi et al., Liu et al., respectively.
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Citation Excerpt :
Nevertheless, cybercriminals can attack such systems for fraudulent purposes [9]. Thus, it is a scientific and technological challenge to develop information security and privacy systems through innovative solutions for e-health systems [10]. In several medical scenarios, multiple biosignals are transmitted from one or multiple users to the corresponding specialist remotely, e.g., in ambulances, home care, hospitals, sport care [11].
E-health provides several remote health services highly convenient for patients. Nevertheless, inherent security risks are present in e-health such as data privacy since insecure communication channels are used to transmit data between patients and physicians or to cloud medical data storage. Nowadays, medical body area network provides a solution to continuous health monitoring with real-time updates of multibiosignal records in multiuser communication schemes for monitoring and early detection of medical conditions or diseases. In this paper, we propose to use chaos-based sequence direct spread spectrum technology and chaos-based cryptography to provide data privacy, high security and efficiency in monitoring multibiosignals in multiuser networks for e-health applications. First, each plain biosignal is modulated with sequence direct spread spectrum by using the chaotic Hénon map. Then, all modulated biosignals are summed to produce the modulated cryptogram. The modulated cryptogram is finally encrypted by using global diffusion process with the chaotic Hénon map to increase security by reducing the high autocorrelation of the modulated cryptogram. The experimental results are presented in a simulated multiuser scenario with 4 users (or patients) and 2 specialists (neurologist and cardiologist), with 12 biosignals acquired from database on the Internet, such as electroencephalograms, electromyograms, blood pressure signals, and electrocardiograms. A comprehensive security study is presented to show the high security, the high speed encryption, and the high noise interference robustness. According with the results, the proposed method can be used for secure multibiosignal monitoring in multiuser networks for e-health applications with high efficiency and security.

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View full text

An enhanced reversible patient data hiding algorithm for E-healthcare

Highlights

Abstract

Introduction

Section snippets

Literature review

Preliminaries

Proposed algorithm

Results and discussion

Conclusion

Declaration of Competing Interest

J. Med. Syst.

Signal Process.

J. Vis. Commun. Image Represent.

Signal Process.

Comput. Methods Programs Biomed.

J. Biomed. Inform.

Pattern Recognit. Lett.

Maturitas

Neurocomputing

Telemedicine by mobile communication

IEEE Eng. Med. Biol. Mag.

An efficient msb prediction-based method for high-capacity reversible data hiding in encrypted images

IEEE Trans. Inf. Forensics Secur.

Reversible data hiding

Reversible data embedding using a difference expansion

IEEE Trans. Circuits Syst. Video Technol.

Reversible data hiding

IEEE Trans. Circuits Syst. Video Technol.

Reversible data hiding using histogram shifting in small blocks