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Author: Françoise Fogelman-Soulié
Publisher: IOS Press
ISBN: 1586038982
Category : Computers
Languages : en
Pages : 388
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Book Description
The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. This book is suitable for those interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.
Author: Françoise Fogelman-Soulié
Publisher: IOS Press
ISBN: 1586038982
Category : Computers
Languages : en
Pages : 388
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Book Description
The real power for security applications will come from the synergy of academic and commercial research focusing on the specific issue of security. This book is suitable for those interested in understanding the techniques for handling very large data sets and how to apply them in conjunction for solving security issues.
Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480
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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Dzejla Medjedovic
Publisher: Simon and Schuster
ISBN: 1638356564
Category : Computers
Languages : en
Pages : 302
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Book Description
Massive modern datasets make traditional data structures and algorithms grind to a halt. This fun and practical guide introduces cutting-edge techniques that can reliably handle even the largest distributed datasets. In Algorithms and Data Structures for Massive Datasets you will learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects—and there’s no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you’ll find the sweet spot of saving space without sacrificing your data’s accuracy. About the technology Standard algorithms and data structures may become slow—or fail altogether—when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost. This unique book distills cutting-edge research papers into practical techniques for sketching, streaming, and organizing massive datasets on-disk and in the cloud. About the book Algorithms and Data Structures for Massive Datasets introduces processing and analytics techniques for large distributed data. Packed with industry stories and entertaining illustrations, this friendly guide makes even complex concepts easy to understand. You’ll explore real-world examples as you learn to map powerful algorithms like Bloom filters, Count-min sketch, HyperLogLog, and LSM-trees to your own use cases. What's inside Probabilistic sketching data structures Choosing the right database engine Designing efficient on-disk data structures and algorithms Algorithmic tradeoffs in massive-scale systems Computing percentiles with limited space resources About the reader Examples in Python, R, and pseudocode. About the author Dzejla Medjedovic earned her PhD in the Applied Algorithms Lab at Stony Brook University, New York. Emin Tahirovic earned his PhD in biostatistics from University of Pennsylvania. Illustrator Ines Dedovic earned her PhD at the Institute for Imaging and Computer Vision at RWTH Aachen University, Germany. Table of Contents 1 Introduction PART 1 HASH-BASED SKETCHES 2 Review of hash tables and modern hashing 3 Approximate membership: Bloom and quotient filters 4 Frequency estimation and count-min sketch 5 Cardinality estimation and HyperLogLog PART 2 REAL-TIME ANALYTICS 6 Streaming data: Bringing everything together 7 Sampling from data streams 8 Approximate quantiles on data streams PART 3 DATA STRUCTURES FOR DATABASES AND EXTERNAL MEMORY ALGORITHMS 9 Introducing the external memory model 10 Data structures for databases: B-trees, Bε-trees, and LSM-trees 11 External memory sorting
Author: Nathalie Japkowicz
Publisher: Springer
ISBN: 3319269895
Category : Technology & Engineering
Languages : en
Pages : 334
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Book Description
This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
Author: Reza Montasari
Publisher: Springer Nature
ISBN: 3031504542
Category : Computers
Languages : en
Pages : 276
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Book Description
This book represents an interdisciplinary academic endeavour intended to provide readers with a comprehensive, balanced, and nuanced examination of critical issues at the intersection of cyberspace, cyberterrorism, and national and international security. It draws insights from a range of diverse fields, including Computer Science, Social Science, Political Science, International Relations, Criminology, and Law. Furthermore, the book investigates the field of Artificial Intelligence (AI) and related technologies, exploring their dual role in this dynamic landscape of contemporary cyberthreats, with both constructive and malicious implications. The book comprises four distinct themes, with each theme represented by a dedicated Part. Within this organisational framework, each overarching theme is systematically explored through a series of chapters, providing readers with a clear and thematic roadmap for their journey through the content. Part I, Understanding Terrorism and Counter-Terrorism Strategies, of the book explores complexities surrounding contemporary global security challenges. It serves as the foundational segment of the book, consisting of three chapters that critically analyse various dimensions of terrorism and the strategies implemented to combat it. Part II, Cyberterrorism Landscape, of the book offers an in-depth assessment of the current cyberterrorism landscape. This section comprises two critical chapters, each contributing to a comprehensive understanding of the contemporary threats posed by cyberterrorism and their implications for national security. Part III, Countering Cyberterrorism with Technology, of the book forms the core of the book’s exploration into leveraging technology to mitigate the threats of cyberterrorism. This section includes four critical chapters, collectively providing an in-depth understanding of the intersection between technology and counterterrorism strategies. Part IV, Artificial Intelligence and National and International Security, of the book delves into the complex relationship between AI technology and the broader security landscape. Comprising three pivotal chapters, this section provides a detailed understanding of AI’s transformative role in shaping the future of national and international security. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. This comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. /divThis comprehensive resource serves as a valuable reference for law enforcement, policymakers, cybersecurity experts, researchers, academics, and technology enthusiasts interested in counter-terrorism efforts. By exploring the intricate landscape of cyberspace, this book equips readers with knowledge essential to addressing the evolving challenges posed by cyber terrorism. /div
Author: Tamane, Sharvari
Publisher: IGI Global
ISBN: 1522524878
Category : Computers
Languages : en
Pages : 325
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Book Description
In recent years, technological advances have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Privacy and Security Policies in Big Data is a pivotal reference source for the latest research on innovative concepts on the management of security and privacy analytics within big data. Featuring extensive coverage on relevant areas such as kinetic knowledge, cognitive analytics, and parallel computing, this publication is an ideal resource for professionals, researchers, academicians, advanced-level students, and technology developers in the field of big data.
Author: Fazli Can
Publisher: Springer
ISBN: 3319059122
Category : Computers
Languages : en
Pages : 375
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Book Description
Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.
Author: Jaideep Vaidya
Publisher: Springer Science & Business Media
ISBN: 0387294899
Category : Computers
Languages : en
Pages : 124
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Book Description
Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
Author: Yuan Tian
Publisher: Springer Nature
ISBN: 9811908524
Category : Computers
Languages : en
Pages : 761
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Book Description
This book constitutes the refereed proceedings of the Third International Conference on Big Data and Security, ICBDS 2021, held in Shenzhen, China, in November 2021 The 46 revised full papers and 13 short papers were carefully reviewed and selected out of 221 submissions. The papers included in this volume are organized according to the topical sections on cybersecurity and privacy; big data; blockchain and internet of things, and artificial intelligence/ machine learning security.
Author: Joshua Saxe
Publisher: No Starch Press
ISBN: 1593278594
Category : Computers
Languages : en
Pages : 274
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Book Description
Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how to: - Analyze malware using static analysis - Observe malware behavior using dynamic analysis - Identify adversary groups through shared code analysis - Catch 0-day vulnerabilities by building your own machine learning detector - Measure malware detector accuracy - Identify malware campaigns, trends, and relationships through data visualization Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.
