Performance Analysis of Image Steganography based on DWT and Arnold Transform

Sharda, Shikha; Budhiraja, Sumit

doi:10.5120/12099-8310

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…Arash Vosoughi, et al, [12] proposed the use of discrete wavelet transform and Wiener filter for speckle noise suppression of ultrasound images. Shikha Sharda, et al, [13] proposed the important methods of steganography and presented the review of steganography in digital images. This paper presents a new steganography method for embedding secret image into cover image with enhanced security.…”

Section: Related Workmentioning

confidence: 99%

“…Cryptography tends to modify the data into a form that an eavesdropper cannot understand. On the other hand, steganography tends to hide the existence of the message itself, which makes it difficult for an observer to find out where the message is [13]. Sometimes, sending encrypted information may draw the attention of an observer, while invisible information will not.…”

Section: Introductionmentioning

confidence: 99%

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Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

Sehgal¹,

Sharma²

2013

IJCA

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Image steganography is the art and science of hiding secret image into digital media such that no one apart from the intended recipient is able to detect the existence of the information. There are many different carriers that can be used to hide the information such as digital images, videos, sound files and other computer files but digital images are the most popular. In this paper, a method has been proposed using which a large size secret image can be hidden into small size cover image securely. The main aim here is the absolute invisibility of the large size secret image. The secret image is first scrambled by using Arnold transformation. Haar Discrete Wavelet Transformation (DWT) is then applied on cover image and Arnold transformed secret image, followed by Alpha Blending operation. Then the Haar Inverse Discrete Wavelet Transformation (IDWT) is applied to obtain the stego image. At the receiver side, first the cover image is obtained from the stego image. Then Haar DWT is applied on the cover image and the stego image followed by the alpha blending operation. Haar IDWT is applied on the resulting image. Then by applying Arnold transformation, the secret image is obtained. The proposed method does not require the sender to send the cover image to the receiver for obtaining the secret image.The performance of the proposed method is investigated by comparing the cover image and the stego image in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Normalized Cross Correlation (NCC). Experimental results demonstrate the effectiveness and accuracy of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

Sehgal¹,

Sharma²

2013

IJCA

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“…Steganography exploit of human perception; our senses aren't made to hunt for files with information concealed inside of them [1].a superb image steganography technique includes three main parts, the first is capacity or the greatest quantity of data that must be held within the cover image, the second factor is imperceptibility which refers to the quality of the stego-picture built after data has been hidden, and the third factor is robustness which measures the ability of secret information to resist against threats [3].The most popular stenographic approach is Least Significant Bit (LSB) substitution. The core notion of LSB substitution entails embedding secret data in bits with the smallest weighting so that the value of the original pixel is unaffected [4]. Steganography methods can be classified into text, image, audio, and video steganography according on the cover media used to embed secret data [3]:…”

Section: Introductionmentioning

confidence: 99%

Hiding Information in Digital Images Using LSB Steganography Technique

Jebur

Nawar

Kadhim

et al. 2023

Int. J. Interact. Mob. Technol.

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The highest way to protect data from intruder and unauthorized persons has become a major issue. This matter led to the development of many techniques for data security, such as Steganography, Cryptography, and Watermarking to disguise data. This paper proposes an image steganography method using the Least Significant Bits (LSB) technique and XOR operator and a secret key, through which the secret key is transformed into a one-dimensional bit stream array, then these bits are XORed with the bits of the secret image. Multiple experiments have been performed to embed color and grayscale images inside cover media. In this work, the LSB technique is ideal in two ways: firstly, only the least significant one-bit (1bit) of each byte will store the embedded data, this method is named (1-LSB). Secondly, the four least significant bits of the right half-byte (4 bits) of each byte will store the embedded data, this method is named (4-LSB). Subjective and objective analyzes were performed for each LSB process. The subjective analysis is responsible for both HVS and histogram, whereas the objective analysis involved both PSNR and MSE metrics.

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“…Steganography is a technique for embedding secret information into an innocent-looking carrier. There are many medium that can be used as carrier, such as videos (Sadek, Khalifa, & Mostafa, 2015), audios (Dutta, Bhattacharyya, & Kim, 2009), images (Sharda & Budhiraja, 2013), et al Video has become one of the most popular carrier for Steganography with the development of multimedia. Video Steganography can easily achieve a large Capacity with slight modification.…”

Section: Introductionmentioning

confidence: 99%

An Intra-Prediction Mode-Based Video Steganography With Secure Strategy

Cao

Sun

Jiang

et al. 2021

International Journal of Digital Crime and Forensics

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In this paper, an intra-prediction mode (IPM)-based video steganography with secure strategy was proposed for H.264 video stream. First of all, according to the property of IPM conversion after calibration, a content-adaptive selection strategy was adopted to measure candidate carrier macroblock. Then, a more efficient encoding strategy based on grouped IPM was applied to encode secret message. This encoding strategy aimed to further enhance the security performance by exploiting the deviation feature of calibrated IPM. Finally, syndrome-trellis code was used as the embedding implementation to minimize distortion. Experimental results demonstrate that this article proposed algorithm presents a novel security performance with any existing IPM-based video steganography.

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Performance Analysis of Image Steganography based on DWT and Arnold Transform

Cited by 8 publications

References 11 publications

Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

Eliminating Cover Image Requirement in Discrete Wavelet Transform based Digital Image Steganography

Hiding Information in Digital Images Using LSB Steganography Technique

An Intra-Prediction Mode-Based Video Steganography With Secure Strategy

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