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.
Fei Hu (University of Alabama Tuscaloosa USA)
Country of Publication:
Further / Higher Education
SECTION I: BIG DATA MANAGEMENT: STORAGE, SHARING, AND PROCESSING Challenges and Approaches in Spatial Big Data Management Ablimit Aji and Fusheng Wang Storage and Database Management for Big Data Vijay Gadepally, Jeremy Kepner, and Albert Reuther Performance Evaluation of Protocols for Big Data Transfers Se-young Yu, Nevil Brownlee, and Aniket Mahanti Challenges in Crawling the Deep Web Yan Wang and Jianguo Lu Big Data and Information Distillation in Social Sensing Dong Wang Big Data and the SP Theory of Intelligence J. Gerard Wolff A Qualitatively Different Principle for the Organization of Big Data Processing Duoduo Liao, Maryam Yammahi, Adi Alhudfhaif, Faisal Alsaby, Usamah AlGemili, and Simon Y. Berkoich SECTION II: BIG DATA SECURITY: SECURITY, PRIVACY, AND ACCOUNTABILITY Integration with Cloud Computing Security Ibrahim A. Gomaa and Emad Abd-Elrahman Toward Reliable and Secure Data Access for Big Data Service Fouad Amine Guenane, Michele Nogueira, Donghyun Kim, and Ahmed Serhrouchni Cryptography for Big Data Security Ariel Hamlin, Nabil Schear, Emily Shen, Mayank Varia, Sophia Yakoubov, and Arkady Yerukhimovich Some Issues of Privacy in a World of Big Data and Data Mining Daniel E. O'Leary Privacy in Big Data Benjamin Habegger, Omar Hasan, Thomas Cerqueus, Lionel Brunie, Nadia Bennani, Harald Kosch, and Ernesto Damiani Privacy and Integrity of Outsourced Data Storage and Processing Dongxi Liu, Shenlu Wang, and John Zic Privacy and Accountability Concerns in the Age of Big Data Manik Lal Das Secure Outsourcing of Data Analysis Jun Sakuma Composite Big Data Modeling for Security Analytics Yuh-Jong Hu and Wen-Yu Liu Exploring the Potential of Big Data for Malware Detection and Mitigation Techniques in Android Environment Rasheed Hussain, Donghyun Kim, Michele Nogueira, Junggab Son, and Heekuck Oh Index
Fei Hu is a professor of electrical and computer engineering at the University of Alabama. Dr. Hu is the author of 10 books and over 200 articles published in top journals and conferences. His current research interests include big data security and 5G networks.