Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/824
Title: Big Digital Forensic Data
Other Titles: Volume 1: Data Reduction Framework and Selective Imaging /
Authors: Quick, Darren. ;;Choo, Kim-Kwang Raymond. ;
subject: Computer Science;Forensic science. ;;Computer Security;Application Software;Computers;Law and legislation. ;;Computer Science;Systems and Data Security;Information Systems Applications;Forensic Science. ;;Legal Aspects of Computing. ;;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
Abstract: This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas. ;
Description: QA76.9.A25 ;
005.8 ; 23 ;

SpringerLink (Online service) ;
Printed edition: ; 9789811077623. ;


URI: http://localhost/handle/Hannan/824
ISBN: 9789811077630 ;
9789811077623 (print) ;
More Information: XV, 96 p. 6 illus., 5 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
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Title: Big Digital Forensic Data
Other Titles: Volume 1: Data Reduction Framework and Selective Imaging /
Authors: Quick, Darren. ;;Choo, Kim-Kwang Raymond. ;
subject: Computer Science;Forensic science. ;;Computer Security;Application Software;Computers;Law and legislation. ;;Computer Science;Systems and Data Security;Information Systems Applications;Forensic Science. ;;Legal Aspects of Computing. ;;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
Abstract: This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas. ;
Description: QA76.9.A25 ;
005.8 ; 23 ;

SpringerLink (Online service) ;
Printed edition: ; 9789811077623. ;


URI: http://localhost/handle/Hannan/824
ISBN: 9789811077630 ;
9789811077623 (print) ;
More Information: XV, 96 p. 6 illus., 5 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9789811077623.pdf3.77 MBAdobe PDFThumbnail
Preview File
Title: Big Digital Forensic Data
Other Titles: Volume 1: Data Reduction Framework and Selective Imaging /
Authors: Quick, Darren. ;;Choo, Kim-Kwang Raymond. ;
subject: Computer Science;Forensic science. ;;Computer Security;Application Software;Computers;Law and legislation. ;;Computer Science;Systems and Data Security;Information Systems Applications;Forensic Science. ;;Legal Aspects of Computing. ;;Computer Appl. in Social and Behavioral Sciences. ;
Year: 2018
place: Singapore :
Publisher: Springer Singapore :
Imprint: Springer,
Series/Report no.: SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
SpringerBriefs on Cyber Security Systems and Networks, ; 2522-5561. ;
Abstract: This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas. ;
Description: QA76.9.A25 ;
005.8 ; 23 ;

SpringerLink (Online service) ;
Printed edition: ; 9789811077623. ;


URI: http://localhost/handle/Hannan/824
ISBN: 9789811077630 ;
9789811077623 (print) ;
More Information: XV, 96 p. 6 illus., 5 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9789811077623.pdf3.77 MBAdobe PDFThumbnail
Preview File