A Novel Data Hiding Approach by Pixel-Value-Difference Steganography and Optimal Adjustment to Secure E-Governance Documents

Halder, Tanmoy Kanti; Karforma, Sunil; Mandal, Rupali

doi:10.17485/ijst/2015/v8i16/51269

Cited by 9 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Step 1.2: Based on local similarity, the predicted value V1, which is calculated using the neighboring pixels and their locational weights, is obtained. At location ①, V1 is calculated as shown in Equation (9). The coordinates of location ① are (xi, yj).…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…Various reversible data hiding techniques have been recently proposed . Various techniques have been proposed to hide data using the least significant bit (LSB) of image pixels [4][5][6][7][8][9]. The data hiding techniques using the LSB of a pixel has a disadvantage in that the restored cover image does not match the original cover image because the LSBs are changed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Jung

2020

Applied Sciences

View full text Add to dashboard Cite

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.

show abstract

Section: Proposed Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Jung

2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Berdasarkan hasil penelitian mereka berhasil menigkatkan kapasitas karena area tepi yang digunakan lebih banyak. Hal itupun berakibat terhadap kualitas gambar yang menurun, ini dibuktikan dari nilai PSNR yang didapat jauh lebih kecil dari hanya menggunakan dua blok piksel [6].…”

Section: Abstrakunclassified

Implementasi Steganografi Dengan Metode Pixel Value Differencing (PVD) pada Gambar JPG dan PNG

Firdaus

Suartana

2020

JINACS

View full text Add to dashboard Cite

Abstrak— Informasi dalam bentuk pesan tidak hanya disandikan, namun dapat juga disisipkan ke dalam citra digital. Teknik menyembunyikan atau menyisipkan pesan disebut steganografi. Steganografi merupakan metode yang digunakan untuk menyembunyikan informasi sehingga informasi yang bersifat rahasia tidak dapat diketahui pihak yang tidak berhak mengetahuinya. Dalam steganografi terdapat beberapa metode yang dapat digunakan dalam mengamankan informasi dari suatu pihak yang tidak berhak mengetahuinya, salah satunya dengan menggunakan metode PVD (Pixel Value Differencing) yang dalam implementasinya memanfaatkan citra digital sebagai media penampung. Penelitian ini bermaksud menghitung kapasitas jumlah bit dan melihat pengaruh format gambar terhadap jumlah kapasitas bit yang dapat disisipi pesan. PVD yang digunakan adalah dengan dua blok piksel untuk mempertahankan kualitas citra hasil steganografi. Hasil dari penelitian ini menunjukkan kapasitas yang didapat pada gambar JPG dan PNG tidak berbeda signifikan. Kemudian juga didapat nilai PSNR (Peak Signal to Noise Ratio) dari gambar JPG dan PNG yang relatif sama diatas 40 dB. Namun metode PVD tidak dapat mengantisipasi perhitungan nilai piksel baru yang melebihi nilai maksimal warna 255 dan tidak memiliki ketahanan terhadap modifikasi hasil steganografi. Kata Kunci— Steganografi, Citra Digital, Pixel Value Differencing, Kapasitas, PSNR.

show abstract

“…the original copy) and Y-channel frame of the encoded/impaired copy. The MSE between the two signals is defined in equation (8) and PSNR is calculated using equation (9). L reflects the range of values that a pixel can take: for example, if the Y channel is encoded with a depth of 8-bit, then L = 2^8 -1 = 255.…”

Section: Proposed Work a Fitness Functionmentioning

confidence: 99%

“…Block of size M*N could be selected, where value of M and N vary from 1 to 7. T.Halder & S.Karforma [8] extended Chi-Shing Chan's method to increase the capacity of blocks. They proposed that, rather than increasing the size of blocks by just modifying the embedding algorithm capacity could be increased.…”

Section: Introductionmentioning

confidence: 99%

A PSO based Information Hiding Approach using Pixel Mapping and Wavelet Transformation

Halder¹,

Karforma²

2018

IJET

Self Cite

View full text Add to dashboard Cite

In this paper a new data hiding approach has been proposed combining Pixel value difference (PVD), Particle swarm optimization (PSO) and pixel mapping. The aim of this paper is to map the secret information within most suitable block of pixels to ensure minimum change. Each pixel groups are different in nature and may not map with any group of secret data. Appropriate mapping of pixels is conducted by verifying some parameters. Collective forms of those parameters create the fitness function. The fitness function of particles is chosen such a way that a balanced ratio between capacity and Signal to Noise Ratio(SNR)is to be maintained. To elevate security level of encryption, overlooking the spatial domain embedding Haar discrete wavelet transformation (DWT) has been used. Embedded images are compared and analysed against existing approaches in term of hiding capacity and induced noise.

show abstract

A Novel Data Hiding Approach by Pixel-Value-Difference Steganography and Optimal Adjustment to Secure E-Governance Documents

Cited by 9 publications

References 9 publications

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

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

Implementasi Steganografi Dengan Metode Pixel Value Differencing (PVD) pada Gambar JPG dan PNG

A PSO based Information Hiding Approach using Pixel Mapping and Wavelet Transformation

Contact Info

Product

Resources

About