Computational Intelligence in the Reversible Data-Hiding Processes Using Radon Transform

2020 ◽  
pp. 414-424
Author(s):  
B. Bazeer Ahamed
Keyword(s):  
Digital Media ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Research Area ◽  
Stego Image ◽  
Host Image ◽  
Confidential Data ◽  
Multimedia Technologies ◽  
Compression Coding ◽  
High Payload

Data hiding has emerged as a major research area due to the phenomenal growth in internet and multimedia technologies. Securing data transmitted over the internet becomes a challenging issue caused in digitization and networking over the past decade. Data hiding schemes have been adopted to protect digital media content which involves confidential data such as text, video, audio, images, and compression coding. A good reversible data hiding scheme is characterized by the possession of attributes like reversible, imperceptible, high payload capacity, and robustness. By reversible, it's meant that the extraction of the payload as well as the restoration of the host image perfectly from the stego image. Secondly, the imperceptible stego image resemblance against the cover/host image. Finally, robustness counts for the ability to sustain the secret payload against both intentional and unintentional attacks; it has been observed that all the proposed algorithms are more robust and reversible against various attacks in lower bit error rate and higher normalization coefficient.

scholarly journals An Advanced Reversible Data Hiding Algorithm Using Local Similarity, Curved Surface Characteristics, and Edge Characteristics in Images

2020 ◽  
Vol 10 (3) ◽  
pp. 836 ◽  
Author(s):  
Soo-Mok Jung ◽  
Byung-Won On
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Image Watermarking ◽  
Surface Characteristics ◽  
Cover Image ◽  
Curved Surface ◽  
Local Similarity ◽  
Stego Image ◽  
Confidential Data ◽  
The Difference

In this paper, we proposed methods to accurately predict pixel values by effectively using local similarity, curved surface characteristics, and edge characteristics present in an image. Furthermore, to hide more confidential data in a cover image using the prediction image composed of precisely predicted pixel values, we proposed an effective data hiding technique that applied the prediction image to the conventional reversible data hiding technique. Precise prediction of pixel values greatly increases the frequency at the peak point in the histogram of the difference sequence generated using the cover and prediction images. This considerably increases the amount of confidential data that can be hidden in the cover image. The proposed reversible data hiding algorithm (ARDHA) can hide up to 24.5% more confidential data than the existing algorithm. Moreover, it is not possible to determine the presence of hidden confidential data in stego-images, as they possess excellent visual quality. The confidential data can be extracted from the stego-image without loss, and the original cover image can be restored from the stego-image without distortion. Therefore, the proposed algorithm can be effectively used in digital image watermarking, military, and medical applications.

Reversible data hiding in an encrypted image using the homomorphic property of elliptic curve cryptography

2021 ◽  
pp. 1-12
Author(s):  
R. Anushiadevi ◽  
Rengarajan Amirtharajan
Keyword(s):  
Elliptic Curve ◽  
Data Hiding ◽  
Elliptic Curve Cryptography ◽  
Reversible Data Hiding ◽  
Cloud Service ◽  
Cover Image ◽  
Stego Image ◽  
Security Applications ◽  
Confidential Data ◽  
Location Map

Reversible Data Hiding (RDH) schemes have recently gained much interest in protecting the secret information and sensitive cover images. For cloud security applications, the third party’s data embedding can be done (e.g., cloud service). In such a scenario, to protect the cover image from unauthorized access, it is essential to encrypt before embedding it. It can be overcome by combining the RDH scheme with encryption. However, the key challenge in integrating RDH with encryption is that the correlation between adjacent pixels begins to disappear after encryption, so reversibility cannot be accomplished. RDH with elliptic curve cryptography is proposed to overcome this challenge. In this paper (ECC-RDH) by adopting additive homomorphism property; the proposed method, the stego image decryption gives the sum of the original image and confidential data. The significant advantages of this method are, the cover image is transferred with high security, the embedding capacity is 0.5 bpp with a smaller location map size of 0.05 bpp. The recovered image and secrets are the same as in the original, and thus 100% reversibility is proved.

A high payload separable reversible data hiding in cipher image with good decipher image quality

2020 ◽  
Vol 38 (5) ◽  
pp. 6403-6414 ◽  
Author(s):  
R. Anushiadevi ◽  
Padmapriya Pravinkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Payload

scholarly journals Reversible Data Hiding Using Two Marked Images Based on Adaptive Coefficient-Shifting Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Ching-Yu Yang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Secret Image Sharing ◽  
Signal To Noise ◽  
Host Medium ◽  
Secret Image ◽  
Image Sharing ◽  
Host Image ◽  
Acs Algorithm

This paper proposes a novel form of reversible data hiding using two marked images by employing the adaptive coefficient-shifting (ACS) algorithm. The proposed ACS algorithm consists of three parts: the minimum-preserved scheme, the minimum-preserved with squeezing scheme, and the base-value embedding scheme. More specifically, each input block of a host image can be encoded to two stego-blocks according to three predetermined rules by the above three schemes. Simulations validate that the proposed method not only completely recovers the host medium but also losslessly extracts the hidden message. The proposed method can handle various kinds of images without any occurrence of overflow/underflow. Moreover, the payload and peak signal-to-noise ratio (PSNR) performance of the proposed method is superior to that of the conventional invertible data hiding schemes. Furthermore, the number of shadows required by the proposed method is less than that required by the approaches which are based upon secret image sharing with reversible steganography.

scholarly journals Taylor expansion based stereo image reversible data hiding

2020 ◽  
Author(s):  
Xinyang Ying ◽  
Guobing Zhou
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Taylor Expansion ◽  
Stereo Image ◽  
Embedding Capacity ◽  
Stereo Images ◽  
Secret Data ◽  
Stego Image ◽  
Multi Level

Abstract The reversible data hiding allows original image to be completely recovered from the stego image when the secret data has been extracted, it is has drawn a lot of attentions from researchers. In this paper, a novel Taylor Expansion (TE) based stereo image reversible data hiding method is presented. Since the prediction accuracy is essential to the data hiding performance, a novel TE based predictor using correlations of two views of the stereo image is proposed. TE can fully exploit strong relationships between matched pixels in the stereo image so that the accuracy of the prediction can be improved. Then, histogram shifting is utilized to embed data to decrease distortion of stereo images, and multi-level hiding can increase embedding capacity. Experimental results show that the proposed method is superior to some existing data hiding methods considering embedding capacity and the quality of the stego stereo images.

scholarly journals An Improved Reversible Image Transformation Using K-Means Clustering and Block Patching

Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 17 ◽  
Author(s):  
Haidong Zhong ◽  
Xianyi Chen ◽  
Qinglong Tian
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Privacy Protection ◽  
Reversible Data Hiding ◽  
Auxiliary Information ◽  
Experimental Results ◽  
Image Transformation ◽  
Clustering Method ◽  
Stego Image ◽  
Encrypted Images

Recently, reversible image transformation (RIT) technology has attracted considerable attention because it is able not only to generate stego-images that look similar to target images of the same size, but also to recover the secret image losslessly. Therefore, it is very useful in image privacy protection and reversible data hiding in encrypted images. However, the amount of accessorial information, for recording the transformation parameters, is very large in the traditional RIT method, which results in an abrupt degradation of the stego-image quality. In this paper, an improved RIT method for reducing the auxiliary information is proposed. Firstly, we divide secret and target images into non-overlapping blocks, and classify these blocks into K classes by using the K-means clustering method. Secondly, we match blocks in the last (K-T)-classes using the traditional RIT method for a threshold T, in which the secret and target blocks are paired with the same compound index. Thirdly, the accessorial information (AI) produced by the matching can be represented as a secret segment, and the secret segment can be hided by patching blocks in the first T-classes. Experimental results show that the proposed strategy can reduce the AI and improve the stego-image quality effectively.

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.

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