A Robust Watermarking Scheme for Online Multimedia Copyright Protection Using New Chaotic Map

Anees, Amir; Hussain, Iqtadar; Algarni, Abdulmohsen; Aslam, Muhammad

doi:10.1155/2018/1840207

Cited by 22 publications

(11 citation statements)

References 29 publications

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“…The proposed is designed specially for those images that consist of a large number of the same patterns. As a lot of mathematical operations are included in the proposed scheme, it is somehow slower than the other existing schemes [13,[44][45][46]. Therefore, the scheme proposed in [18] is not suitable for real-time applications.…”

Section: Image Encryption In Frequency Domainmentioning

confidence: 99%

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

Shafique

Mehmood

Alawida

et al. 2022

Wireless Communications and Mobile Computing

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The Internet of Things connects billions of intelligent devices that can interact with one another without human intervention, and during communication, a large amount of data is exchanged between the devices. As a result, it is critical to secure digital data using an encryption technique that provides a suitable degree of security. Numerous existing encryption techniques do not offer sufficient security. Therefore, it is critical to figure out which encryption technique is most appropriate for a particular kind of data. When it comes to manually deciding which encryption technique to use, the process might take a long time. In this research, we present a novel technique for selecting Encryption Algorithms (EAs) based on a particular application using pattern recognition and machine learning techniques. To accomplish this goal, we also prepare a dataset. Several machine learning techniques, such as Support Vector Machines (SVMs), Linear Regression (LR), K -Nearest Neighbour (KNN), Naïve Bayes (NB), Decision Trees (DT), and Random Forests (RF), are evaluated. Based on the evaluation, the SVM has been chosen as the best option for the intended technique because its classification accuracy is 98.7%. The experimental results, including accuracy, precision, recall, and F1-score, are used to gauge the performance of the suggested technique. The proposed technique is also compared with the existing techniques to demonstrate its effectiveness.

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Section: Image Encryption In Frequency Domainmentioning

confidence: 99%

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

Shafique

Mehmood

Alawida

et al. 2022

Wireless Communications and Mobile Computing

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“…Hybrid combination of Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption is proposed to counter the security issues in multimedia data. Graph Based Transform (GBT) is a transform that uses signal in the form of graph and produces better results in terms of adapting signal structure of an image [35]. GBT is used as it is robust against various attack scenarios in the field of image processing.…”

Section: E Proposed Technique Of Watermarkingmentioning

confidence: 99%

A Secured Frame Selection Based Video Watermarking Technique to Address Quality Loss of Data: Combining Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption

Sharma

Bagga

Sobti

et al. 2021

Security and Communication Networks

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The advancement of Internet technologies has led to the availability of audios, images, and videos in different forms. The unauthorized users are exploiting the use of multimedia by transmitting them on various Internet sites to earn money unethically without the intervention of the original copyright holder. Watermarking is a technique used to hide the signal known as watermark inside multimedia data that is not visible to the intruder to manipulate any information. In this paper, a secured watermarking approach is developed to tackle issues related to copyright protection and ownership identification. A Secured Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption hybrid techniques are proposed. The watermark cannot be embedded in every frame of the video as it adds to the size of the video and watermark can be easily retrieved by an intruder. Therefore, the frame selection algorithm has been proposed in the given work. Adding watermark in the frame adds to the challenge of quality loss. The quality loss is addressed in this work. Various attacks have been applied on the watermarked frames to calculate the performance of the proposed technique using quality metrics: Peak Signal to Noise Ratio, Structural Similarity Index, Normalized Correlation, and Bit Error Rate. The results indicate that the proposed technique is effective against various attack scenarios.

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“…We have used C-LM in our proposed encryption algorithm. Using C-LM over logistic map [57] is that C-LM is the modified form of a logistic map and gives better results than the chaotic logistic map. The C-LM is given as: [58]:…”

Section: A Cubic-logistic Map (C-lm)mentioning

confidence: 99%

Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain

et al. 2021

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In this paper, a noise-resistant image encryption scheme is proposed. We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a "sandwich encryption." The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme's performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible.INDEX TERMS Discrete Wavelet Transform (DWT), Chaotic map, Medical images, Bit-plane decomposition, Security analysis of medical images.

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A Robust Watermarking Scheme for Online Multimedia Copyright Protection Using New Chaotic Map

Cited by 22 publications

References 29 publications

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

A Novel Machine Learning Technique for Selecting Suitable Image Encryption Algorithms for IoT Applications

A Secured Frame Selection Based Video Watermarking Technique to Address Quality Loss of Data: Combining Graph Based Transform, Singular Valued Decomposition, and Hyperchaotic Encryption

Noise-Resistant Image Encryption Scheme for Medical Images in the Chaos and Wavelet Domain

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