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Titlebook: Combating Security Challenges in the Age of Big Data; Powered by State-of- Zubair Md. Fadlullah,Al-Sakib Khan Pathan Book 2020 Springer Nat

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書(shū)目名稱Combating Security Challenges in the Age of Big Data
副標(biāo)題Powered by State-of-
編輯Zubair Md. Fadlullah,Al-Sakib Khan Pathan
視頻videohttp://file.papertrans.cn/230/229844/229844.mp4
概述Offers a comprehensive coverage of the main topic, ranging from big data analytics to protection.Provides an up-to-date source on computing/network security and resilience contributed by international
叢書(shū)名稱Advanced Sciences and Technologies for Security Applications
圖書(shū)封面Titlebook: Combating Security Challenges in the Age of Big Data; Powered by State-of- Zubair Md. Fadlullah,Al-Sakib Khan Pathan Book 2020 Springer Nat
描述.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 authenticat
出版日期Book 2020
關(guān)鍵詞Big Data Analytics and Security; Cloud Computing Resiliency; Internet of Things Security; Blockchain Ba
版次1
doihttps://doi.org/10.1007/978-3-030-35642-2
isbn_softcover978-3-030-35644-6
isbn_ebook978-3-030-35642-2Series ISSN 1613-5113 Series E-ISSN 2363-9466
issn_series 1613-5113
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Wissen, Kommunikation und Gesellschafttion exits which reasons that the data is a random variable which is being generated independently from an underlying stationary distribution. In this chapter we present discussions on concept drifts that are inherent in the context big data. We discuss different forms of concept drifts that are evi
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https://doi.org/10.1007/978-3-531-90761-1utilization will increase the value of information and on the other hand also induces an increase in the number of attacks on such systems. Side Channel Attack (SCA) is an attack model that could disrupt the information security when hardware implements a cryptographic algorithm. Differential Power
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https://doi.org/10.1007/978-3-658-33768-1g. It is considered as one of the prime issues regarding cyber world security. Damage caused by the malware programs ranges from system failure to financial loss. Traditional approach for malware classification approach are not very suitable for advance malware programs. For the continuously evolvin
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https://doi.org/10.1007/978-3-322-82663-3e of the inter-machine communication, which is popularly referred to as the Machine to Machine (M2M) communications whereby the deployed “things” such as smart meters and numerous sensors require none/minimal human intervention to characterize power requirements and energy distribution. The plethora
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