Due to the significant advancement of the Internet of Things (IoT) in the healthcare sector, the security, and the integrity of the medical data became big challenges for healthcare services applications. This paper proposes a hybrid security model for securing the diagnostic text data in medical images. The proposed model is developed through integrating either 2-D discrete wavelet transform 1 level (2D-DWT-1L) or 2-D discrete wavelet transform 2 level (2D-DWT-2L) steganography technique with a proposed hybrid encryption scheme. The proposed hybrid encryption schema is built using a combination of Advanced Encryption Standard, and Rivest, Shamir, and Adleman algorithms. The proposed model starts by encrypting the secret data; then it hides the result in a cover image using 2D-DWT-1L or 2D-DWT-2L. Both color and gray-scale images are used as cover images to conceal different text sizes. The performance of the proposed system was evaluated based on six statistical parameters; the peak signal-to-noise ratio (PSNR), mean square error (MSE), bit error rate (BER), structural similarity (SSIM), structural content (SC), and correlation. The PSNR values were relatively varied from 50.59 to 57.44 in case of color images and from 50.52 to 56.09 with the gray scale images. The MSE values varied from 0.12 to 0.57 for the color images and from 0.14 to 0.57 for the gray scale images. The BER values were zero for both images, while SSIM, SC, and correlation values were ones for both images. Compared with the state-of-the-art methods, the proposed model proved its ability to hide the confidential patient’s data into a transmitted cover image with high imperceptibility, capacity, and minimal deterioration in the received stego-image.

/pdf/secure-medical-data-transmission-model-for-iot-based-57stlk1cx6.pdf

Secure Medical Data Transmission Model for IoT-Based Healthcare Systems

Deep learning technologies, which are the key components of state-of-the-art Artificial Intelligence (AI) services, have shown great success in providing human-level capabilities for a variety of tasks, such as visual analysis, speech recognition, and natural language processing and etc. Building a production-level deep learning model is a non-trivial task, which requires a large amount of training data, powerful computing resources, and human expertises. Therefore, illegitimate reproducing, distribution, and the derivation of proprietary deep learning models can lead to copyright infringement and economic harm to model creators. Therefore, it is essential to devise a technique to protect the intellectual property of deep learning models and enable external verification of the model ownership. In this paper, we generalize the "digital watermarking'' concept from multimedia ownership verification to deep neural network (DNNs) models. We investigate three DNN-applicable watermark generation algorithms, propose a watermark implanting approach to infuse watermark into deep learning models, and design a remote verification mechanism to determine the model ownership. By extending the intrinsic generalization and memorization capabilities of deep neural networks, we enable the models to learn specially crafted watermarks at training and activate with pre-specified predictions when observing the watermark patterns at inference. We evaluate our approach with two image recognition benchmark datasets. Our framework accurately (100%) and quickly verifies the ownership of all the remotely deployed deep learning models without affecting the model accuracy for normal input data. In addition, the embedded watermarks in DNN models are robust and resilient to different counter-watermark mechanisms, such as fine-tuning, parameter pruning, and model inversion attacks.

Protecting Intellectual Property of Deep Neural Networks with Watermarking

The VLDB journal : the international journal on very large data bases.

Copyright protection and proof of ownership are two of the main important applications of the digital image watermarking. The challenges faced by researchers interested in digital image watermarking applications lie in the creation of new algorithms to serve those applications and to be resistant to most types of attacks, especially the geometrical attacks. Robustness, high imperceptibility, security, and large capacity are four essential requirements in any watermarking scheme. This paper presents a new image watermarking scheme based on the Redundant Discrete Wavelet Transform (RDWT) and the Singular Value Decomposition (SVD). The gray scale image watermark was embedded directly in the singular values of the RDWT sub-bands of the host image. The scheme achieved a large capacity due to the redundancy in the RDWT domain and at the same time preserved high imperceptibility due to SVD properties. Embedding the watermarking pixel's values without any modification inside the wavelet coefficient of the host image overcomes the security issue. Furthermore, the experimental results of the proposed scheme showed a high level of robustness not only against the image processing attacks but also against the geometrical attacks which are considered as difficult attacks to resist.

Robust blind image watermarking scheme based on Redundant Discrete Wavelet Transform and Singular Value Decomposition

This paper presents a novel blind watermarking algorithm in DCT domain using the correlation between two DCT coefficients of adjacent blocks in the same position. One DCT coefficient of each block is modified to bring the difference from the adjacent block coefficient in a specified range. The value used to modify the coefficient is obtained by finding difference between DC and median of a few low frequency AC coefficients and the result is normalized by DC coefficient. The proposed watermarking algorithm is tested for different attacks. It shows very good robustness under JPEG image compression as compared to existing one and also good quality of watermark is extracted by performing other common image processing operations like cropping, rotation, brightening, sharpening, contrast enhancement etc.

A novel blind robust image watermarking in DCT domain using inter-block coefficient correlation

The proliferation of digitized media due to the rapid growth of networked multimedia systems, has created an urgent need for copyright enforcement technologies that can protect copyright ownership of multimedia objects. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system. In this paper, we describe an imperceptible and a robust combined DWT-DCT digital image watermarking algorithm. The algorithm watermarks a given digital image using a combination of the Discrete Wavelet Transform (DWT) and the Discrete Cosine Transform (DCT). Performance evaluation results show that combining the two transforms improved the performance of the watermarking algorithms that are based solely on the DWT transform.

Combined DWT-DCT Digital Image Watermarking

An improved SVD-based watermarking scheme for protecting rightful ownership

Hiding information in an image in a way that does not affect the original cover image pixels or cause a permanent distortion after extracting that information is known as reversible data hiding technology. Many reversible data hiding schemes have been proposed and successfully applied in medical and military applications. Such schemes are developed to ensure digital images' authenticity and integrity without any distortion on the original images. They guarantee that any attempt to change the watermarked image will be detected by the image owner. In this paper, a novel algorithm is proposed to reversibly hide data into encrypted grayscale medical images in a separable manner. The proposed algorithm hides two watermarks in a given encrypted image. The first watermark is embedded by replacing selected encrypted image pixels based on data hiding key, and the second watermark is embedded in the watermarked encrypted image using the histogram shifting reversible data hiding method. The experimental results demonstrate that the proposed algorithm has high embedding capacity, high visual image quality, and high entropy.

Reversible data hiding in encrypted images

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video, however, few algorithms have been proposed for audio watermarking. This is due to the fact that, the human audio system is far more complex and sensitive than the human visual system. In this paper, we describe an imperceptible and robust audio watermarking algorithm based on the discrete wavelet transform. Performance of the algorithm has been evaluated extensively, and simulation results are presented to demonstrate the imperceptibility and robustness of the proposed algorithm.

DWT-Based Audio Watermarking

Medical images exchanged over public networks require a methodology to provide confidentiality for the image, authenticity of the image ownership and source of origin, and image integrity verification. To provide these three security requirements, we propose in this paper a region-based algorithm based on multiple watermarking in the frequency and spatial domains. Confidentiality and authenticity are provided by embedding robust watermarks in the region-of-non-interest (RONI) of the image using a blind scheme in the discrete wavelet transform and singular value decomposition domain (DWT-SVD). On the other hand, integrity is provided by embedding local fragile watermarks in the region-of-interest (ROI) of the image using a reversible scheme in the spatial domain. The integrity provided by the proposed algorithm is implemented on a block-level of the partitioned-image, thus enabling localized detection of tampered regions. The algorithm was evaluated with respect to imperceptibility, robustness, capacity, and tamper localization capability, using MRI, Ultrasound, and X-ray gray-scale medical images. Performance results demonstrate the effectiveness of the proposed algorithm in providing the required security services for telemedicine applications.

/pdf/secured-telemedicine-using-region-based-watermarking-with-36asxt2fnw.pdf

Ali Al-Haj

Papers

Combined DWT-DCT Digital Image Watermarking

An improved SVD-based watermarking scheme for protecting rightful ownership

Reversible data hiding in encrypted images

DWT-Based Audio Watermarking

Secured Telemedicine Using Region-Based Watermarking with Tamper Localization