Big.Data.Storage.Sharing.and.Security

【文件属性】：
文件名称：Big.Data.Storage.Sharing.and.Security
文件大小：7.88MB
文件格式：PDF
更新时间：2020-01-10 10:21:07
Big Data Storage Security Although there are already some books published on Big Data, most of them only cover basic concepts and society impacts and ignore the internal implementation details―making them unsuitable to R&D people. To fill such a need, Big Data: Storage, Sharing, and Security examines Big Data management from an R&D perspective. It covers the 3S designs―storage, sharing, and security―through detailed descriptions of Big Data concepts and implementations. Written by well-recognized Big Data experts around the world, the book contains more than 450 pages of technical details on the most important implementation aspects regarding Big Data. After reading this book, you will understand how to: Aggregate heterogeneous types of data from numerous sources, and then use efficient database management technology to store the Big Data Use cloud computing to share the Big Data among large groups of people Protect the privacy of Big Data during network sharing With the goal of facilitating the scientific research and engineering design of Big Data systems, the book consists of two parts. Part I, Big Data Management, addresses the important topics of spatial management, data transfer, and data processing. Part II, Security and Privacy Issues, provides technical details on security, privacy, and accountability. Examining the state of the art of Big Data over clouds, the book presents a novel architecture for achieving reliability, availability, and security for services running on the clouds. It supplies technical descriptions of Big Data models, algorithms, and implementations, and considers the emerging developments in Big Data applications. Each chapter includes references for further study. Table of Contents Section I: Big data management: Storage, Sharing, and Processing Chapter 1. Challenges and Approaches in Spatial Big Data Management Chapter 2. Storage and Database Management for Big Data Chapter 3. Performance Evaluation of Protocols for Big Data Transfers Chapter 4. Challenges in Crawling the Deep Web Chapter 5. Big Data and Information Distillation in Social Sensing Chapter 6. Big Data and the SP Theory of Intelligence Chapter 7. A Qualitatively Different Principle for the Organization of Big Data Processing Section II: Big Data Security: Security, Privacy, and Accountability Chapter 8. Integration with Cloud Computing Security Chapter 9. Toward Reliable and Secure Data Access for Big Data Service Chapter 10. Cryptography for Big Data Security Chapter 11. Some Issues of Privacy in a World of Big Data and Data Mining Chapter 12. Privacy in Big Data Chapter 13. Privacy and Integrity of Outsourced Data Storage and Processing Chapter 14. Privacy and Accountability Concerns in the Age of Big Data Chapter 15. Secure Outsourcing of Data Analysis Chapter 16. Composite Big Data Modeling for Security Analytics Chapter 17. Exploring the Potential of Big Data for Malware Detection and Mitigation Techniques in the Android Environment