Matrix Coding-Based Quantum Image Steganography Algorithm

Qu, Zhiguo; Cheng, Zhenwen; Wang, Xiaojun

doi:10.1109/access.2019.2894295

Cited by 40 publications

(19 citation statements)

References 30 publications

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“…Zhiguo Qu, Zhenwen CHENG and Xiaojun Wang proposed two different implying style. One implying methodology is single pixel-inserted coding, referred to as SPE secret writing for brief, the second embedding methodology is that the multiple pixels inserted coding, referred to as MPsE coding [16]. Namita Tiwari and Madhu Shandilya two suggested ways to show RGB image information, one is the pixel pointer technology and the other is a triple algorithm A.…”

Section: Related Workmentioning

confidence: 99%

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Neamah¹,

Abed²,

Abbood³

2020

IJECE

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At the moment, with the great development of information and communications technology, the transfer of confidential and sensitive data through public communications such as the Internet is very difficult to keep them from hackers and attackers. Therefore, it is necessary to work on the development of new and innovative ways to transfer such information and protect it to ensure that it reaches the desired goal. The goal of a new technique to hide information design not only hides the secret message behind the center cover, but it also provides increased security. The most common way to transfer important and confidential data is through embedding it into cover medium files in a way that does not affect the accuracy of the carrier file, which is known as hiding. In this paper, encryption and concealment techniques were used to protect data transferred from attackers. The proposed method relied on encryption of confidential information using the encryption key and the Xnor gate, after which the encrypted information was hidden in a color image using the LSB algorithm. The method of concealment depends on the extraction of chromatic channels of three RGB for each pixel and specifying the channel in which the bit of the encryption message will be hidden. Some metrics have been adopted to measure the quality of the resulting picture after hiding as PSNR and MSE, and achieve good results.

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Section: Related Workmentioning

confidence: 99%

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Neamah¹,

Abed²,

Abbood³

2020

IJECE

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“…Secondly, a quantum watermarking approach is used to hide a water-marked gray image to a carrier image. Qo et al proposed a quantum steganography approach using matrix coding for quantum color images [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Secure Transmission of Data Using Image Steganography

Chandra¹,

Paira²

2019

IJIVP

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Data is one of the most relevant and important term from the ancient Greek age to modern science and business. The amount of data and use of data transformation for organizational work is increasing. So, for the sake of security and to avoid data loss and unauthorized access of data we have designed an image Steganographic algorithm implementing both Cryptography and Steganography. This algorithm imposed a cipher text within a cover image to conceal the existence of the cipher text and the stego-image is transferred from sender to intended receiver by invoking a distributed connection among them to achieve the data authenticity.

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“…us, a new research hotspot, quantum machine learning [27][28][29][30][31][32], has gradually formed. Although quantum technology provides a certain improvement in storage and computing power, the "curse of dimensionality" problem still exists in quantum machine learning.…”

Section: Introductionmentioning

confidence: 99%

Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing

et al. 2020

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The complex systems with edge computing require a huge amount of multifeature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational efficiency and save the resource consumption. In this paper, a quantum-based feature selection algorithm for the multiclassification problem, namely, QReliefF, is proposed, which can effectively reduce the complexity of algorithm and improve its computational efficiency. First, all features of each sample are encoded into a quantum state by performing operations CMP and Ry, and then the amplitude estimation is applied to calculate the similarity between any two quantum states (i.e., two samples). According to the similarities, the Grover–Long method is utilized to find the nearest k neighbor samples, and then the weight vector is updated. After a certain number of iterations through the above process, the desired features can be selected with regards to the final weight vector and the threshold τ. Compared with the classical ReliefF algorithm, our algorithm reduces the complexity of similarity calculation from O(MN) to O(M), the complexity of finding the nearest neighbor from O(M) to OM, and resource consumption from O(MN) to O(MlogN). Meanwhile, compared with the quantum Relief algorithm, our algorithm is superior in finding the nearest neighbor, reducing the complexity from O(M) to OM. Finally, in order to verify the feasibility of our algorithm, a simulation experiment based on Rigetti with a simple example is performed.

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Matrix Coding-Based Quantum Image Steganography Algorithm

Cited by 40 publications

References 30 publications

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

Secure Transmission of Data Using Image Steganography

Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing

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