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Mohamed Elhoseny

Bio: Mohamed Elhoseny is an academic researcher from Mansoura University. The author has contributed to research in topics: Computer science & Encryption. The author has an hindex of 49, co-authored 240 publications receiving 7044 citations. Previous affiliations of Mohamed Elhoseny include Maharaja Agrasen Institute of Technology & Cairo University.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: The proposed hybrid security model for securing the diagnostic text data in medical images 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.
Abstract: 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.

414 citations

Journal ArticleDOI
TL;DR: Experimental results demonstrate that the proposed feature selection method effectively reduces the dimensions of the dataset and achieves superior classification accuracy using the selected features.

353 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the current literature on integration of CC and IoT to solving various problems in healthcare applications such as smart hospitals, medicine control, and remote medical services and a new concept of the integration ofCC and IoT for healthcare applications, called the CloudIoT-Health paradigm is presented.
Abstract: Cloud Computing (CC) and the Internet of Things (IoT) have emerged as new platforms in the ICT revolution of the twenty-first century. The adoption of the CloudIoT paradigm in the healthcare field can bring several opportunities to medical IT, and experts believe that it can significantly improve healthcare services and contribute to its continuous and systematic innovation. This paper presents a comprehensive review of the current literature on integration of CC and IoT to solving various problems in healthcare applications such as smart hospitals, medicine control, and remote medical services. Also, a brief introduction to cloud computing and internet of things with an application to health care is given. This paper presents a new concept of the integration of CC and IoT for healthcare applications, which is what we; call the CloudIoT-Health paradigm. The term CloudIoT-Health and some key integration issues are presented in this paper to offer a practical vision to integrate current components of CC and the IoT in healthcare applications. Also, this paper aims to present the state of the art and gap analysis of different levels of integration components, analyzing different existing proposals in CloudIoT-Health systems. Finally, related researches of CC and IoT integration for healthcare systems have been reviewed. Challenges to be addressed and future directions of research are identified, and an extensive bibliography is presented.

286 citations

Journal ArticleDOI
TL;DR: A new model to optimize virtual machines selection in cloud-IoT health services applications to efficiently manage a big amount of data in integrated industry 4.0 applications is proposed and outperforms on the state-of-the-art models in total execution time and the system efficiency.

249 citations

Journal ArticleDOI
TL;DR: An intelligent model based on the Genetic Algorithm to organize bank lending decisions in a highly competitive environment with a credit crunch constraint (GAMCC), which provides a framework to optimize bank objectives when constructing the loan portfolio.
Abstract: The bank lending decisions in credit crunch environments are big challenge.This NP-hard optimization problem is solved using a proposed GA based model.The proposed model is tested using two scenarios with simulated and real data.The real data is collected from Southern Louisiana Credit Union.The proposed model increased the bank profit and improved the system performance. To avoid the complexity and time consumption of traditional statistical and mathematical programming, intelligent techniques have gained great attention in different financial research areas, especially in banking decisions optimization. However, choosing optimum bank lending decisions that maximize the bank profit in a credit crunch environment is still a big challenge. For that, this paper proposes an intelligent model based on the Genetic Algorithm (GA) to organize bank lending decisions in a highly competitive environment with a credit crunch constraint (GAMCC). GAMCC provides a framework to optimize bank objectives when constructing the loan portfolio, by maximizing the bank profit and minimizing the probability of bank default in a search for a dynamic lending decision. Compared to the state-of-the art methods, GAMCC is considered a better intelligent tool that enables banks to reduce the loan screening time by a range of 12%50%. Moreover, it greatly increases the bank profit by a range of 3.9%8.1%.

210 citations


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01 Jan 2004
TL;DR: Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance and describes numerous important application areas such as image based rendering and digital libraries.
Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

3,627 citations

01 Jun 2005

3,154 citations

01 Sep 2008
TL;DR: The Methodology used to Prepare the Guideline Epidemiology Incidence Etiology and Recommendations for Assessing Response to Therapy Suggested Performance Indicators is summarized.
Abstract: Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators

2,961 citations