Vai al contenuto principale della pagina

Big Digital Forensic Data [[electronic resource] ] : Volume 1: Data Reduction Framework and Selective Imaging / / by Darren Quick, Kim-Kwang Raymond Choo



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Quick Darren Visualizza persona
Titolo: Big Digital Forensic Data [[electronic resource] ] : Volume 1: Data Reduction Framework and Selective Imaging / / by Darren Quick, Kim-Kwang Raymond Choo Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018
Edizione: 1st ed. 2018.
Descrizione fisica: 1 online resource (109 pages)
Disciplina: 363.25968
Soggetto topico: Computer security
Application software
Forensic science
Computers
Law and legislation
Systems and Data Security
Information Systems Applications (incl. Internet)
Forensic Science
Legal Aspects of Computing
Computer Appl. in Social and Behavioral Sciences
Persona (resp. second.): ChooKim-Kwang Raymond
Nota di contenuto: Chapter 1 Introduction -- Chapter 2 Background and Literature Review -- Chapter 3 Data Reduction and Data Mining Framework -- Chapter 4 Digital Forensic Data Reduction by Selective Imaging -- Chapter 5 Summary of the Framework and DRbSI.
Sommario/riassunto: 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.
Titolo autorizzato: Big Digital Forensic Data  Visualizza cluster
ISBN: 981-10-7763-0
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299287503321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: SpringerBriefs on Cyber Security Systems and Networks, . 2522-5561