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Data analytics for cybersecurity /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data analytics for cybersecurity // Vandana P. Janeja.
作者:	Janeja, Vandana P.,
出版者:	Cambridge ;Cambridge University Press, : c2022.,
面頁冊數:	xiii, 192 p. :ill. ; : 24 cm.;
標題:	Data mining. -
ISBN:	9781108415279 (hbk.) :

Data analytics for cybersecurity /
Janeja, Vandana P.,1976-

Data analytics for cybersecurity /Vandana P. Janeja. - Cambridge ;Cambridge University Press,c2022. - xiii, 192 p. :ill. ;24 cm.

Includes bibliographical references and index.

Introduction - data analytics for cybersecurity -- Understanding sources of cybersecurity data -- Introduction to data mining : clustering, classification and association rule mining -- Big data analytics and its need for cybersecurity -- Types of cyber attacks -- Anomaly detection for cyber security -- Anomaly detection -- Cybersecurity through time series and spatial data -- Cybersecurity through network and graph data -- Human centered data analytics for cyber security -- Future directions in data analytics for cybersecurity.

As 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.

ISBN: 9781108415279 (hbk.) :NT2165 Subjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.A25 / J37 2022

Dewey Class. No.: 005.8

Data analytics for cybersecurity /
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245 1 0 $a Data analytics for cybersecurity / $c Vandana P. Janeja.
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504 $a Includes bibliographical references and index.
505 0 # $a Introduction - data analytics for cybersecurity -- Understanding sources of cybersecurity data -- Introduction to data mining : clustering, classification and association rule mining -- Big data analytics and its need for cybersecurity -- Types of cyber attacks -- Anomaly detection for cyber security -- Anomaly detection -- Cybersecurity through time series and spatial data -- Cybersecurity through network and graph data -- Human centered data analytics for cyber security -- Future directions in data analytics for cybersecurity.
520 # $a As 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.
650 # 0 $a Data mining. $3 528622
650 # 0 $a Computer security $x Data processing. $3 1235103