東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Big Data/Analytics." ]

切換: 標籤 | MARC模式 | ISBD

Data analytics and decision support ...

Palomares Carrascosa, Ivan.

FindBook

Google Book

Amazon

博客來

Data analytics and decision support for cybersecurity = trends, methodologies and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data analytics and decision support for cybersecurity/ edited by Ivan Palomares Carrascosa, Harsha Kumara Kalutarage, Yan Huang.
其他題名:	trends, methodologies and applications /
其他作者:	Palomares Carrascosa, Ivan.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xvi, 270 p. :ill., digital ;24 cm.
內容註:	A Toolset for Intrusion and Insider Threat Detection -- Human-Machine Decision Support Systems for Insider Threat Detection -- Detecting malicious collusions between mobile software applications -- Dynamic Analysis of Malware using Run-Time Opcodes -- Big Data Analytics for Intrusion Detection System: Statistical Decision-making using Finite Dirichlet Mixture Models -- Security of Online Examinations -- Attribute Noise, Classification Technique, and Classification Accuracy -- Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbances of Cyber-Attacks in Smart Power Systems using Gaussian Processes and Fuzzy Inference -- Visualization and Data Provenance Trends in Decision Support for Cybersecurity.
Contained By:	Springer eBooks
標題:	Computer security - Decision making. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-59439-2
ISBN:	9783319594392

Data analytics and decision support for cybersecurity = trends, methodologies and applications /
Data analytics and decision support for cybersecuritytrends, methodologies and applications /[electronic resource] :edited by Ivan Palomares Carrascosa, Harsha Kumara Kalutarage, Yan Huang. - Cham :Springer International Publishing :2017. - xvi, 270 p. :ill., digital ;24 cm. - Data analytics,2520-1859. - Data analytics..

A Toolset for Intrusion and Insider Threat Detection -- Human-Machine Decision Support Systems for Insider Threat Detection -- Detecting malicious collusions between mobile software applications -- Dynamic Analysis of Malware using Run-Time Opcodes -- Big Data Analytics for Intrusion Detection System: Statistical Decision-making using Finite Dirichlet Mixture Models -- Security of Online Examinations -- Attribute Noise, Classification Technique, and Classification Accuracy -- Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbances of Cyber-Attacks in Smart Power Systems using Gaussian Processes and Fuzzy Inference -- Visualization and Data Provenance Trends in Decision Support for Cybersecurity.

The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring. Researchers and professionals alike will find the chapters an essential read for further research on the topic.

ISBN: 9783319594392

Standard No.: 10.1007/978-3-319-59439-2doiSubjects--Topical Terms:

3251584
Computer security
--Decision making.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Data analytics and decision support for cybersecurity = trends, methodologies and applications /
LDR:03293nmm a2200337 a 4500 001 2106081
003 DE-He213
005 20180313120356.0
006 m d
007 cr nn 008maaau
008 180417s2017 gw s 0 eng d
020 $a 9783319594392 $q (electronic bk.)
020 $a 9783319594385 $q (paper)
024 7 $a 10.1007/978-3-319-59439-2 $2 doi
035 $a 978-3-319-59439-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A25
072 7 $a UNF $2 bicssc
072 7 $a UYQE $2 bicssc
072 7 $a COM021030 $2 bisacsh
082 0 4 $a 005.8 $2 23
090 $a QA76.9.A25 $b D232 2017
245 0 0 $a Data analytics and decision support for cybersecurity $h [electronic resource] : $b trends, methodologies and applications / $c edited by Ivan Palomares Carrascosa, Harsha Kumara Kalutarage, Yan Huang.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xvi, 270 p. : $b ill., digital ; $c 24 cm.
490 1 $a Data analytics, $x 2520-1859
505 0 $a A Toolset for Intrusion and Insider Threat Detection -- Human-Machine Decision Support Systems for Insider Threat Detection -- Detecting malicious collusions between mobile software applications -- Dynamic Analysis of Malware using Run-Time Opcodes -- Big Data Analytics for Intrusion Detection System: Statistical Decision-making using Finite Dirichlet Mixture Models -- Security of Online Examinations -- Attribute Noise, Classification Technique, and Classification Accuracy -- Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbances of Cyber-Attacks in Smart Power Systems using Gaussian Processes and Fuzzy Inference -- Visualization and Data Provenance Trends in Decision Support for Cybersecurity.
520 $a The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring. Researchers and professionals alike will find the chapters an essential read for further research on the topic.
650 0 $a Computer security $x Decision making. $3 3251584
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Data Encryption. $3 891254
650 2 4 $a Big Data/Analytics. $3 2186785
700 1 $a Palomares Carrascosa, Ivan. $3 3251582
700 1 $a Kalutarage, Harsha Kumara. $3 3251583
700 1 $a Huang, Yan. $3 784621
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Data analytics. $3 3242868
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-59439-2
950 $a Computer Science (Springer-11645)