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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Machine Learning for Authorship Attribution and Cyber Forensics
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Machine Learning for Authorship Attribution and Cyber Forensics
Benjamin C. M. Fung (Gebundene Ausgabe, Englisch)
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Beschreibung
The book first explores the cybersecurity’s landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and… digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potentialsuspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
05.12.2020
Sprache
Englisch
EAN
9783030616748
Herausgeber
Springer International Publishing
Serien- oder Bandtitel
International Series on Computer, Entertainment and Media Technology
Sonderedition
Nein
Autor
Benjamin C. M. Fung
Seitenanzahl
158
Auflage
1st edition 2020
Einbandart
Gebundene Ausgabe
Schlagwörter
Cybercrime, Forensic investigation, Cyber forensics, Crime investigation, Data mining, Classification, Clustering, Authorship analysis, Statistical analysis, Authorship identification, Authorship characterization, Rule mining, Cybercrimes, Criminal networks, Writeprint, Stylometric features, Anonymity, Associative classification
Thema-Inhalt
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
UYQM - Maschinelles Lernen
LNQE - Computer- und Internetkriminalität
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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