The Experts below are selected from a list of 310275 Experts worldwide ranked by ideXlab platform
Ahmed Farouk - One of the best experts on this subject based on the ideXlab platform.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
Mohamed Elhoseny - One of the best experts on this subject based on the ideXlab platform.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
R B Arps - One of the best experts on this subject based on the ideXlab platform.
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applications of universal context modeling to lossless compression of gray scale Images
IEEE Transactions on Image Processing, 1996Co-Authors: M J Weinberger, Jorma Rissanen, R B ArpsAbstract:Inspired by theoretical results on universal modeling, a general framework for sequential modeling of Gray-Scale Images is proposed and applied to lossless compression. The model is based on stochastic complexity considerations and is implemented with a tree structure. It is efficiently estimated by a modification of the universal algorithm context. Several variants of the algorithm are described. The sequential, lossless compression schemes obtained when the context modeler is used with an arithmetic coder are tested with a representative set of Gray-Scale Images. The compression ratios are compared with those obtained with state-of-the-art algorithms available in the literature, with the results of the comparison consistently favoring the proposed approach.
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applications of universal context modeling to lossless compression of gray scale Images
Asilomar Conference on Signals Systems and Computers, 1995Co-Authors: M J Weinberger, Jorma Rissanen, R B ArpsAbstract:Inspired by theoretical results on universal modeling, a general framework for sequential modeling of Gray-Scale Images is proposed and applied to lossless compression. The model is based on stochastic complexity considerations and is implemented with a tree structure. It is efficiently estimated by a modification of the universal algorithm context. The sequential, lossless compression schemes obtained when the context modeler is used with an arithmetic coder, are tested with a representative set of Gray-Scale Images. The compression ratios are compared with those obtained with state-of-the-art algorithms available in the literature, with the results of the comparison, showing the potential of the proposed approach.
N Arunkumar - One of the best experts on this subject based on the ideXlab platform.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
Shihab A Shawkat - One of the best experts on this subject based on the ideXlab platform.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
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secure medical data transmission model for iot based healthcare systems
IEEE Access, 2018Co-Authors: Mohamed Elhoseny, Gustavo Ramirezgonzalez, Osama M Abuelnasr, Shihab A Shawkat, N Arunkumar, Ahmed FaroukAbstract: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.
