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Data Analytics for Cybersecurity by Vandana P. Janeja (2022, Hardcover)

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About this product

Product Identifiers

PublisherCambridge University Press

ISBN-10110841527X

ISBN-139781108415279

eBay Product ID (ePID)28057257811

Product Key Features

Number of Pages240 Pages

LanguageEnglish

Publication NameData Analytics for Cybersecurity

Publication Year2022

SubjectSecurity / General, General

FeaturesNew Edition

TypeTextbook

Subject AreaMathematics, Computers

AuthorVandana P. Janeja

FormatHardcover

Dimensions

Item Height0.7 in

Item Length9.3 in

Item Width6.2 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2021-046596

Reviews'The intersection of cybersecurity and big data is an operational and analytical capability still very much in its infancy. Data Analytics for Cybersecurity is perfectly positioned as a useful and necessary primer on the subject by exploring this relationship in clear, understandable language and imparts to readers not only the fundamentals of cybersecurity analytics from an academic perspective, but also, if not perhaps more importantly, how this capability relates to and can enhance cybersecurity in actual practice.' Richard Forno, University of Maryland Baltimore County, 'Dr. Janeja shows us how data analytics can be used to predict, identify and intercept threats, solving difficult cybersecurity problems in the process. As a Professor and cybersecurity professional, I am thrilled for the prospect of teaching this material to my students and applying it to the industry at large. Simply put, this is the cybersecurity book I've been looking for.' Faisal Quader, Technuf LLC

Dewey Edition23

IllustratedYes

Dewey Decimal005.8

Table Of ContentPreface; 1. Introduction; 2. Understanding sources of cybersecurity data; 3. Introduction to data mining: clustering, classification and association rule mining; 4. Big data analytics and its need for cybersecurity: advanced DM and complex data types from cybersecurity perspective; 5. Types of Cyber Attacks; 6. Anomaly Detection for cyber security; 7. Anomaly Detection; 8. Cybersecurity through Time Series and Spatial data; 9. Cybersecurity through Network and Graph Data; 10. Human Centered Data Analytics for Cyber security; 11. Future directions in Data Analytics for Cybersecurity; References; Index;

Edition DescriptionNew Edition

SynopsisAs the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity., This data-oriented approach to studying cyber threats shows in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

LC Classification NumberQA76.9.A25J37 2022