Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling
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| Title: | Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling |
|---|---|
| Description: | This book is a practical handbook of research on dealing with mathematical methods in crime prevention for special agents, and discusses their capabilities and benefits that stem from integrating statistical analysis and predictive modeling. It consists of a current collection of research with contributions by authors from different nations in different disciplines. After reading this book, the reader should be able to understand the fundamental nature of cyberspace; understand the role of cyber-attacks; learn analytical techniques and the challenges of predicting events; learn how languages and culture are influenced by cyberspace; and learn techniques of the cyberspace public opinion detection and tracking process. Understanding cyberspace is the key to defending against digital attacks. This book takes a global perspective, examining the skills needed to collect and analyze event information and perform threat or target analysis duties in an effort to identify sources for signs of compromise, unauthorized activity and poor security practices. The ability to understand and react to events in cyberspace in a timely and appropriate manner will be key to future success. Most of the collections are research-based practices that have been done throughout the years. The authors hope that the presented work will be of great use to police investigators and cyber special agents interested in predictive analytics. |
| Authors: | Kuk, Kristijan, Randjelovic, Dragan |
| Resource Type: | eBook. |
| Subjects: | Computer crimes--Investigation, Data mining |
| Categories: | BUSINESS & ECONOMICS / Infrastructure, SOCIAL SCIENCE / General |
| Database: | eBook Collection (EBSCOhost) |
| FullText | Links: – Type: ebook-pdf Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling – Name: Abstract Label: Description Group: Ab Data: This book is a practical handbook of research on dealing with mathematical methods in crime prevention for special agents, and discusses their capabilities and benefits that stem from integrating statistical analysis and predictive modeling. It consists of a current collection of research with contributions by authors from different nations in different disciplines. After reading this book, the reader should be able to understand the fundamental nature of cyberspace; understand the role of cyber-attacks; learn analytical techniques and the challenges of predicting events; learn how languages and culture are influenced by cyberspace; and learn techniques of the cyberspace public opinion detection and tracking process. Understanding cyberspace is the key to defending against digital attacks. This book takes a global perspective, examining the skills needed to collect and analyze event information and perform threat or target analysis duties in an effort to identify sources for signs of compromise, unauthorized activity and poor security practices. The ability to understand and react to events in cyberspace in a timely and appropriate manner will be key to future success. Most of the collections are research-based practices that have been done throughout the years. The authors hope that the presented work will be of great use to police investigators and cyber special agents interested in predictive analytics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Kuk%2C+Kristijan%22">Kuk, Kristijan</searchLink><br /><searchLink fieldCode="AR" term="%22Randjelovic%2C+Dragan%22">Randjelovic, Dragan</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+crimes--Investigation%22">Computer crimes--Investigation</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22BUSINESS+%26+ECONOMICS+%2F+Infrastructure%22">BUSINESS & ECONOMICS / Infrastructure</searchLink><br /><searchLink fieldCode="ZK" term="%22SOCIAL+SCIENCE+%2F+General%22">SOCIAL SCIENCE / General</searchLink> |
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| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 363.25968 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Computer crimes--Investigation Type: general – SubjectFull: Data mining Type: general Titles: – TitleFull: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kuk, Kristijan – PersonEntity: Name: NameFull: Randjelovic, Dragan – PersonEntity: Name: NameFull: Kuk, Kristijan – PersonEntity: Name: NameFull: Randjelovic, Dragan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2017 – D: 14 M: 03 Type: profile Y: 2017 Identifiers: – Type: isbn-print Value: 9781536105667 – Type: isbn-electronic Value: 9781536105704 Titles: – TitleFull: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling Type: main |
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