Wednesday, December 2, 2020

Privacy-Enhancing Fog Computing and Its Applications PDF Download

Privacy-Enhancing Fog Computing and Its Applications PDF
By:Xiaodong Lin,Jianbing Ni,Xuemin (Sherman) Shen
Published on 2018-11-20 by Springer

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This SpringerBrief covers the security and privacy challenges in fog computing, and proposes a new secure and privacy-preserving mechanisms to resolve these challenges for securing fog-assisted IoT applications. Chapter 1 introduces the architecture of fog-assisted IoT applications and the security and privacy challenges in fog computing. Chapter 2 reviews several promising privacy-enhancing techniques and illustrates examples on how to leverage these techniques to enhance the privacy of users in fog computing. Specifically, the authors divide the existing privacy-enhancing techniques into three categories: identity-hidden techniques, location privacy protection and data privacy enhancing techniques. The research is of great importance since security and privacy problems faced by fog computing impede the healthy development of its enabled IoT applications. With the advanced privacy-enhancing techniques, the authors propose three secure and privacy-preserving protocols for fog computing applications, including smart parking navigation, mobile crowdsensing and smart grid. Chapter 3 introduces identity privacy leakage in smart parking navigation systems, and proposes a privacy-preserving smart parking navigation system to prevent identity privacy exposure and support efficient parking guidance retrieval through road-side units (fogs) with high retrieving probability and security guarantees. Chapter 4 presents the location privacy leakage, during task allocation in mobile crowdsensing, and propose a strong privacy-preserving task allocation scheme that enables location-based task allocation and reputation-based report selection without exposing knowledge about the location and reputation for participators in mobile crowdsensing. Chapter 5 introduces the data privacy leakage in smart grid, and proposes an efficient and privacy-preserving smart metering protocol to allow collectors (fogs) to achieve real-time measurement collection with privacy-enhanced data aggregation. Finally, conclusions and future research directions are given in Chapter 6. This brief validates the significant feature extension and efficiency improvement of IoT devices without sacrificing the security and privacy of users against dishonest fog nodes. It also provides valuable insights on the security and privacy protection for fog-enabled IoT applications. Researchers and professionals who carry out research on security and privacy in wireless communication will want to purchase this SpringerBrief. Also, advanced level students, whose main research area is mobile network security will also be interested in this SpringerBrief.

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Book ID of Privacy-Enhancing Fog Computing and Its Applications's Books is qk11uwEACAAJ, Book which was written byXiaodong Lin,Jianbing Ni,Xuemin (Sherman) Shenhave ETAG "04U4m9MC2oc"

Book which was published by Springer since 2018-11-20 have ISBNs, ISBN 13 Code is 9783030021122 and ISBN 10 Code is 3030021122

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Deep Learning for Medical Image Analysis PDF Download

Deep Learning for Medical Image Analysis PDF
By:S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Published on 2017-01-18 by Academic Press

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Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache

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Book ID of Deep Learning for Medical Image Analysis's Books is WVqfDAAAQBAJ, Book which was written byS. Kevin Zhou,Hayit Greenspan,Dinggang Shenhave ETAG "x2IhZuqPHgQ"

Book which was published by Academic Press since 2017-01-18 have ISBNs, ISBN 13 Code is 9780128104095 and ISBN 10 Code is 0128104090

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Anonymizing Health Data PDF Download

Anonymizing Health Data PDF
By:Khaled El Emam,Luk Arbuckle
Published on 2013-12-11 by |O'Reilly Media, Inc.|

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Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets

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Book which was published by |O'Reilly Media, Inc.| since 2013-12-11 have ISBNs, ISBN 13 Code is 9781449363031 and ISBN 10 Code is 1449363032

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Medical Data Privacy Handbook PDF Download

Medical Data Privacy Handbook PDF
By:Aris Gkoulalas-Divanis,Grigorios Loukides
Published on 2015-11-26 by Springer

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This handbook covers Electronic Medical Record (EMR) systems, which enable the storage, management, and sharing of massive amounts of demographic, diagnosis, medication, and genomic information. It presents privacy-preserving methods for medical data, ranging from laboratory test results to doctors’ comments. The reuse of EMR data can greatly benefit medical science and practice, but must be performed in a privacy-preserving way according to data sharing policies and regulations. Written by world-renowned leaders in this field, each chapter offers a survey of a research direction or a solution to problems in established and emerging research areas. The authors explore scenarios and techniques for facilitating the anonymization of different types of medical data, as well as various data mining tasks. Other chapters present methods for emerging data privacy applications and medical text de-identification, including detailed surveys of deployed systems. A part of the book is devoted to legislative and policy issues, reporting on the US and EU privacy legislation and the cost of privacy breaches in the healthcare domain. This reference is intended for professionals, researchers and advanced-level students interested in safeguarding medical data.

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Book ID of Medical Data Privacy Handbook's Books is g-ALCwAAQBAJ, Book which was written byAris Gkoulalas-Divanis,Grigorios Loukideshave ETAG "8QJjWif2WCY"

Book which was published by Springer since 2015-11-26 have ISBNs, ISBN 13 Code is 9783319236339 and ISBN 10 Code is 3319236334

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Essentials of Computers for Nurses PDF Download

Essentials of Computers for Nurses PDF
By:Virginia K. Saba,Kathleen Ann McCormick
Published on 1996 by McGraw-Hill Companies

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As computers continue to become more common in the health care industry, computer literacy has become an integral part of the nursing profession. Selected Book of the Year by the American Journal of Nursing in its first edition, this book continues to provide an introduction to computer technology for nurses.

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Computer Graphics Using Java 2D and 3D PDF Download

Computer Graphics Using Java 2D and 3D PDF
By:Hong Zhang,Y. Daniel Liang
Published on 2007 by Prentice Hall

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This Java handbook makes a practical tutorial on Java 2D and Java 3D for computer professionals. It contains in-depth coverage of basic computer graphics concepts and techniques, and introduces advanced graphic features to an audience mostly trained in the Java language. Chapter topics include mathematical background for computer graphics, .geometric transformation, views, lighting and texturing, behavior and interaction, and animation.For computer programmers and engineers, data analysts, graphic designers/animators, and game developers.

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Book which was published by Prentice Hall since 2007 have ISBNs, ISBN 13 Code is 9780130351180 and ISBN 10 Code is 0130351180

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