Combating Security Challenges in the Age of Big Data
Springer International Publishing (Verlag)
978-3-030-35641-5 (ISBN)
This book addresses the key security challenges in the big data centric computing and network systems, and discusses how to tackle them using a mix of conventional and state-of-the-art techniques. The incentive for joining big data and advanced analytics is no longer in doubt for businesses and ordinary users alike. Technology giants like Google, Microsoft, Amazon, Facebook, Apple, and companies like Uber, Airbnb, NVIDIA, Expedia, and so forth are continuing to explore new ways to collect and analyze big data to provide their customers with interactive services and new experiences. With any discussion of big data, security is not, however, far behind. Large scale data breaches and privacy leaks at governmental and financial institutions, social platforms, power grids, and so forth, are on the rise that cost billions of dollars.
The book explains how the security needs and implementations are inherently different at different stages of the big data centric system, namely at the point of big data sensing and collection, delivery over existing networks, and analytics at the data centers. Thus, the book sheds light on how conventional security provisioning techniques like authentication and encryption need to scale well with all the stages of the big data centric system to effectively combat security threats and vulnerabilities. The book also uncovers the state-of-the-art technologies like deep learning and blockchain which can dramatically change the security landscape in the big data era.
Zubair Md. Fadlullah is an Associate Professor at the Graduate School of Information Sciences (GSIS), Tohoku University, Japan. Previously he worked at GSIS as an Assistant Professor since 2011 to 2017. Assistant Professor at the Graduate School of Information Sciences (GSIS), Tohoku University, Japan. He also served as a computer science faculty member at the prestigious international Islamic University of Technology (IUT) in Bangladesh. He is a Senior Member of IEEE and ComSoc. Dr. Fadlullah holds a PhD in Applied Information Sciences, obtained in March 2011, from Tohoku University. He has a noteworthy contribution toward research community through his technical papers in scholarly journals, magazines, and international conferences in various areas of networking and communications. He is author of several books and has also co-edited a number of books. As a recognition of his outstanding research contributions, he was awarded the prestigious Dean's and President's awards from Tohoku University in March 2011. He received the IEEE COMSOC Asia Pacific Young Researcher award in 2015. He received the NEC Research Encouragement Award in 2016. He was also acclaimed with the best paper awards in several conferences including ICNDC'16, GLOBECOM'14, and IWCMC'09. He has received research startup funding in 2011-2012, WAKATE-B funding during 2013-2016, and WAKTE-A funding for 2017-2019 under the Grants-in-Aid for Scientific Research (Kakenhi) program from the Japan Society for the Promotion of Science. He was a member of the Japanese team involved with the prestigious A3 Foresight Project supported by Japan Society for the Promotion of Science (JSPS), NSFC of China, and NRF of Korea, that comprised prominent researchers in the field of networking and communications from the mentioned countries.Fadlullah is the General Chair of the SG-IOT'18 conference to be held in Ontario, Canada, in July 2018. He was the General Chair of SG-IOT'17 and a co-chair in the AHSN symposium of IEEE ICC'14 and a chair in the invited session on smart grid in WCSP'11. He has been serving as technical committee member for several IEEE GC, ICC, PIMRC, WCNC, and WCSP conferences for a number of years He is currently serving as Editor of the IEEE Internet of Things (IoT) Journal, IEEE Transactions of Vehicular Technology (TVT), and IEEE Network Magazine. He is also a Co-EiC of Journal of Computers and Applications, Taylor & Francis, UK. He also served as an Editor of the Ad hoc sensor and wireless networks (AHSWN) journal. He has also been actively engaged in helping editorial members of prestigious IEEE transactions (including TVT, TPDS, TSG) to manage and delegate reviews in an efficient manner. He was recipient of the Meritorious Service Certificate as "Top Quality Reviewer" awarded by the IEEE TPDS. His research covers a wide range of areas including smart grid, energy efficiency in wireless networks, sensor and ad hoc networking, network security, and application of game theory in computer networking problems.
Secure Big data Transmission with Trust management for the Internet of Things (IoT).- Concept Drift for Big Data.- Classification of Outlier's Detection Methods Based on Quantitative Or Semantic Learning.- Cognitive Artificial Intelligence Countermeasure For Enhancing The Security Of Big Data Hardware From Power Analysis Attack.- On the Secure Routing Protocols, Selfishness Mitigation, and Trust in Mobile Ad Hoc Networks.- Deep Learning Approaches For IoT Security In The Big Data Era.- Deep Learning meets Malware Detection: An Investigation.- The Utilization of Blockchain for Enhancing Big Data Security and Veracity.- Authentication Methodology for Securing Machine-to-Machine Communication in Smart Grid.- Combating Intrusions in Smart Grid: Practical Defense and Forecasting Approaches.- Blockchain-based Distributed Key Management Approach Tailored for Smart Grid.
Erscheinungsdatum | 28.05.2020 |
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Reihe/Serie | Advanced Sciences and Technologies for Security Applications |
Zusatzinfo | XVI, 266 p. 124 illus., 83 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 600 g |
Themenwelt | Informatik ► Netzwerke ► Sicherheit / Firewall |
Schlagworte | Artificial Intelligence Techniques • Big Data Analytics and Security • Blockchain Based Security and Privacy • Cloud Computing Resiliency • Cyber physical system • Deep Learning for Security • early warning systems • heterogeneous networks • Information Fusion • Intelligent Intrusion Detection and Prevention Met • Intelligent Intrusion Detection and Prevention Methods • Internet of Things Security • sensor networks |
ISBN-10 | 3-030-35641-8 / 3030356418 |
ISBN-13 | 978-3-030-35641-5 / 9783030356415 |
Zustand | Neuware |
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