scholarly journals Reversible difference expansion multi-layer data hiding technique for medical images

2021 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Pascal Maniriho ◽  
Leki Jovial Mahoro ◽  
Zephanie Bizimana ◽  
Ephrem Niyigaba ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Data Communication ◽  
Low Complexity ◽  
Difference Expansion ◽  
Stego Image ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Private Data

Maintaining the privacy and security of confidential information in data communication has always been a major concern. It is because the advancement of information technology is likely to be followed by an increase in cybercrime, such as illegal access to sensitive data. Several techniques were proposed to overcome that issue, for example, by hiding data in digital images. Reversible data hiding is an excellent approach for concealing private data due to its ability to be applied in various fields. However, it yields a limited payload and the quality of the image holding data (Stego image), and consequently, these two factors may not be addressed simultaneously. This paper addresses this problem by introducing a new non-complexity difference expansion (DE) and block-based reversible multi-layer data hiding technique constructed by exploring DE. Sensitive data are embedded into the difference values calculated between the original pixels in each block with relatively low complexity. To improve the payload capacity, confidential data are embedded in multiple layers of grayscale medical images while preserving their quality. The experiment results prove that the proposed technique has increased the payload with an average of 369999 bits and kept the peak signal to noise ratio (PSNR) to the average of 36.506 dB using medical images' adequate security the embedded private data. This proposed method has improved the performance, especially the secret size, without reducing much the quality. Therefore, it is suitable to use for relatively big payloads.

scholarly journals Confidential Health Care Data Exchange Between Multiple Entities in Cloud using Block Chain

2019 ◽  
Vol 9 (2) ◽  
pp. 2566-2573
Keyword(s):  
Health Care ◽  
Data Exchange ◽  
Health Care Organizations ◽  
Main Concept ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Health Care Data ◽  
Private Data ◽  
Peer Network ◽  
Block Chain

Data in the cloud is leading to the more interest for cyber attackers. These days’ attackers are concentrating more on Health care data. Through data mining performed on health care data Industries are making Business out of it. These changes are affecting the treatment process for many people so careful data processing is required. Breaking these data security leads to many consequences for health care organizations. After braking security computation of private data can be performed. By data storing and running of computation on a sensitive data can be possible by decentralization through peer to peer network. Instead of using the centralized architecture by decentralization the attacks can be reduced. Different security algorithms have been considered. For decentralization we are using block chain technology. Privacy, security and integrity can be achieved by this block chain technology. Many solutions have been discussed to assure the privacy and security for Health care organizations somehow failed to address this problem. Many cryptographic functions can be used for attaining privacy of data. Pseudonymity is the main concept we can use to preserve the health care means preserving data by disclosing true identity legally.

scholarly journals A Cryptographic based Approach for Data Hiding in Advanced Video Sequences

2021 ◽  
Vol 12 (6) ◽  
pp. 2031-2038
Author(s):  
Vinay D R, Dr. Anand Babu J
Keyword(s):  
Data Hiding ◽  
Signal To Noise Ratio ◽  
Video Quality ◽  
Similarity Index ◽  
Data Communication ◽  
Structural Similarity ◽  
Video Stream ◽  
Video Sequences ◽  
Video Streams ◽  
Hiding Capacity

Data hiding in video streams became more popular in the present world, since there is a high frequency of data communication over the internet. Hiding the data in video streams provides more security as well as increases embedding capacity than hiding inside the images. The quantity of information to be embedded into the video increases, it can badly influence the video excellence make it inappropriate for certain appliances. The main concerns in data hiding in videos are its high visual excellence, increased hiding capacity, video stream size etc. In this paper, a new data hiding technique is proposed in compressed H.264 Video Streams. At first, the information to be embedded is encrypted using Cryptography approach. The Cryptographic approach helps to encrypt the plain information based on the elliptic points produced by choosing the large prime number. The encrypted data is embedded into the transformed DCT coefficients of I, B and P video frames. The experiment is conducted for different set of video sequences. The results shows that the proposed method yields better performance in terms of Peak signal to noise ratio (PSNR), Structural similarity index (SSIM) and Video quality measure (VQM) when compare to existing methods.

Reversible data hiding method based on pixel expansion and homomorphic encryption

2020 ◽  
Vol 39 (3) ◽  
pp. 2977-2990
Author(s):  
R. Anushiadevi ◽  
Padmapriya Praveenkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Homomorphic Encryption ◽  
Secret Message ◽  
Pixel Expansion ◽  
Stego Image ◽  
Encrypted Image ◽  
Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

scholarly journals Reed Solomon Coding-Based Medical Image Data Hiding Method against Salt and Pepper Noise

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 899 ◽  
Author(s):  
Mehmet Zeki Konyar ◽  
Sıtkı Öztürk
Keyword(s):  
Data Hiding ◽  
Patient Information ◽  
Medical Images ◽  
Experimental Studies ◽  
Secret Message ◽  
Salt And Pepper Noise ◽  
Patient Privacy ◽  
Secret Data ◽  
Stego Image ◽  
Salt And Pepper

Medical data hiding is used to hide patient information inside medical images to protect patient privacy. Patient information in the image should be protected when sending medical images to other specialists or hospitals over the communication network. However, the images are exposed to various unwanted disruptive signals in the communication channel. One of these signals is salt and pepper noise. A pixel exposed to salt and pepper noise becomes completely black or completely white. In pixel-based data hiding methods, it is not possible to extract the secret message in the pixel exposed to this kind of noise. While current data hiding methods are good for many disruptive effects, they are weak against salt and pepper noise. For this reason, the proposed study especially focuses on the accurate extraction of patient information in the salt and pepper noisy medical images. This study was proposed for the most accurate extraction of secret message despite salt and pepper noise, by use of a Reed Solomon error control coding-based data hiding method. The most important feature of Reed Solomon codes is that they can correct errors in non-binary (decimal) numbers directly. Therefore, the Reed Solomon coding-based data hiding method that proposed in this study increases the resistance against salt and pepper noise. Experimental studies show that secret data is accurately extracted from stego images with various densities of salt and pepper noise. Stego medical images created by the proposed method have superior quality values compared to similar literature studies. Additionally, compared to similar methods, the secret message is extracted from the noisy stego image with higher accuracy.

scholarly journals Histogram-based multilayer reversible data hiding method for securing secret data

2019 ◽  
Vol 8 (3) ◽  
pp. 1128-1134
Author(s):  
Chaidir Chalaf Islamy ◽  
Tohari Ahmad
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Histogram Shifting ◽  
Secret Data ◽  
Stego Image ◽  
Sensitive Data ◽  
Modern Age ◽  
Potential Methods

In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.

scholarly journals STEGANOGRAFI PADA CITRA BITMAP MENGGUNAKAN METODE LEAST SIGNIFICANT BIT BERSILANG UNTUK TEKS TERENKRIPSI BASE64

2019 ◽  
Vol 17 (1) ◽  
pp. 73
Author(s):  
Albert Christie Giovani ◽  
Yustina Retno Wahyu Utami ◽  
Teguh Susyanto
Keyword(s):  
Signal To Noise Ratio ◽  
Data Communication ◽  
Text Messages ◽  
Ease Of Use ◽  
The Internet ◽  
Binary Number ◽  
Least Significant Bit ◽  
Stego Image ◽  
Internet Crime ◽  
Internet Media

The development of internet has become one of the most popular data communication media. The ease of use and complete facilities are the advantages possessed by the internet. However, along with the development of internet media and applications that use the Internet,  crime on information system increases as well. With various illegal information-gathering techniques developing, many are trying to access information that is not their right. There are several security techniques for sending messages confidentially and securedly, one of which is known as steganography. This study combined steganography and cryptography. The message was encrypted first using base64 then inserted using the LSB Crossed method. This method was aimed at making the process of extracting messages by unauthorized ones not easy. Embedding message into images was using the last binary number of the RGB value of an image by randomizing the placement of binary numbers by integrating base64 coding so that it combined base64 messages which next the text messages would be encrypted. The measurement results in the stego image using PSNR (Peak Signal to Noise Ratio) showed that the image quality after the insertion process was > 50 db

scholarly journals A secure cloud system for maintaining COVID-19 patient's data using image steganography

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Nandhini Subramanian ◽  
Somaya Al-Maadeed
Keyword(s):  
Deep Learning ◽  
Image Steganography ◽  
Cover Image ◽  
Main Concern ◽  
Stego Image ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Private Patient ◽  
Hiding Capacity ◽  
Smart Healthcare

Background: The COVID-19 pandemic has been life-threatening for many people and as such, a contactless medical system is necessary to prevent the spread of the virus. Smart healthcare systems collect data from patients at one end and process the acquired data at the other end. The cloud is the central point and the communication happens through insecure channels. The main concern, in this case, is the violation of privacy and security as the channel is untrusted. Traditional methods do not provide enough hiding capacity, security, and robustness. This work proposes an image steganography method using the deep learning method to hide the patient's medical images inside an innocent cover image in such a way that they are not visible to human eyes which reduces the suspicions of the presence of sensitive data. Methods: An auto encoder-decoder-based model is proposed with three components: the pre-processing module, the embedding network, and the extraction network. Features from the cover image and the secret images are extracted and fused to reconstruct the stego image. The stego image is then used to extract the ingrained secret image.shows the overall system workflow. Results: Peak Signal-to-Noise Ratio (PSNR) is the evaluation metrics used. The ImageNet dataset was used for training and testing the proposed model.shows the image results of the proposed method. Conclusion: During a COVID-19 screening test, private patient data such as mobile number and Qatari identity card are collected, transferred, and stored through untrusted channels. It is of paramount importance to preserve the privacy, security, and confidentiality of the collected patient records. A secure deep learning-based image steganography method is proposed to secure the sensitive data transferred through untrusted channels in a cloud-based system.

Data Hiding Based on Improved Exploiting Modification Direction Method and Huffman Coding

2014 ◽  
Vol 23 (4) ◽  
pp. 451-459 ◽  
Author(s):  
Ali M. Ahmad ◽  
Ghazali Sulong ◽  
Amjad Rehman ◽  
Mohammed Hazim Alkawaz ◽  
Tanzila Saba
Keyword(s):  
Data Hiding ◽  
Signal To Noise Ratio ◽  
Huffman Coding ◽  
Secret Message ◽  
Least Significant Bit ◽  
Stego Image ◽  
Trade Offs ◽  
Secret Code ◽  
Exploiting Modification Direction ◽  
Emd Method

AbstractThe rapid growth of covert activities via communications network brought about an increasing need to provide an efficient method for data hiding to protect secret information from malicious attacks. One of the options is to combine two approaches, namely steganography and compression. However, its performance heavily relies on three major factors, payload, imperceptibility, and robustness, which are always in trade-offs. Thus, this study aims to hide a large amount of secret message inside a grayscale host image without sacrificing its quality and robustness. To realize the goal, a new two-tier data hiding technique is proposed that integrates an improved exploiting modification direction (EMD) method and Huffman coding. First, a secret message of an arbitrary plain text of characters is compressed and transformed into streams of bits; each character is compressed into a maximum of 5 bits per stream. The stream is then divided into two parts of different sizes of 3 and 2 bits. Subsequently, each part is transformed into its decimal value, which serves as a secret code. Second, a cover image is partitioned into groups of 5 pixels based on the original EMD method. Then, an enhancement is introduced by dividing the group into two parts, namely k1 and k2, which consist of 3 and 2 pixels, respectively. Furthermore, several groups are randomly selected for embedding purposes to increase the security. Then, for each selected group, each part is embedded with its corresponding secret code by modifying one grayscale value at most to hide the code in a (2ki + 1)-ary notational system. The process is repeated until a stego-image is eventually produced. Finally, the χ2 test, which is considered one of the most severe attacks, is applied against the stego-image to evaluate the performance of the proposed method in terms of its robustness. The test revealed that the proposed method is more robust than both least significant bit embedding and the original EMD. Additionally, in terms of imperceptibility and capacity, the experimental results have also shown that the proposed method outperformed both the well-known methods, namely original EMD and optimized EMD, with a peak signal-to-noise ratio of 55.92 dB and payload of 52,428 bytes.

Medical Image Reliability Verification Using Hash Signatures and Sequential Square Encoding

2018 ◽  
Vol 27 (1) ◽  
pp. 19-30
Author(s):  
J. Jennifer Ranjani ◽  
M. Babu
Keyword(s):  
Data Hiding ◽  
Medical Image ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Random Sequence ◽  
Region Of Interest ◽  
Critical Issue ◽  
Hiding Capacity ◽  
Random Sequence Generation ◽  
Image Integrity

Abstract Increased growth of information technology in healthcare has led to a situation where the security of patient information is more important and is a critical issue. The aim of the proposed algorithm is to provide a framework to verify the integrity of the medical images. In this paper, the integrity of the medical images is verified by embedding hash signatures using the sequential square embedding technique. This technique is as efficient as the diamond encoding technique but with increased payload capability. The medical image is first divided into the region of interest (ROI) block and the signature block. The hash signatures are determined by dividing the ROI into nonoverlapping blocks. During the data hiding stage, the hash signatures are embedded in randomly chosen pixel pairs in the signature block using the sequential square encoding (SSE) technique. In the experimental results, the data hiding capacity of the proposed SSE technique is verified in terms of peak signal-to-noise ratio. Also, the medical image integrity is substantiated by comparing the L2 norm between computed and extracted hash signatures. Modifications such as contrast enhancement, rotation, scaling, and changing the image information result in increased L2 norm; thus, the integrity of the medical images can be verified. The parameters required for embedding, such as the embedding parameter and the seed for random sequence generation, are encrypted and communicated to the receiving end. Hence, the proposed algorithm provides a secure framework for medical image integrity verification.

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