A Workbench for Inventing and Sharing Digital Forensic Technology
Buch, Englisch, 352 Seiten, Format (B × H): 192 mm x 236 mm, Gewicht: 619 g
ISBN: 978-0-12-418676-7
Verlag: Syngress Media,U.S.
Rapid development of new cybercrime investigation tools is an essential ingredient in virtually every case and environment. Whether you are performing post-mortem investigation, executing live triage, extracting evidence from mobile devices or cloud services, or you are collecting and processing evidence from a network, Python forensic implementations can fill in the gaps.
Drawing upon years of practical experience and using numerous examples and illustrative code samples, author Chet Hosmer discusses how to:
- Develop new forensic solutions independent of large vendor software release schedules
- Participate in an open-source workbench that facilitates direct involvement in the design and implementation of new methods that augment or replace existing tools
- Advance your career by creating new solutions along with the construction of cutting-edge automation solutions to solve old problems
Zielgruppe
Cybercrime and digital forensic investigators, forensic analysts, software developers, e-discovery researchers, security managers. Secondary audience post graduate and undergraduate students.
Autoren/Hrsg.
Fachgebiete
- Rechtswissenschaften Wirtschaftsrecht Medienrecht Telekommunikationsrecht, IT-Recht, Internetrecht
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Computerkriminalität & Hacking
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein Rechtliche Aspekte der EDV
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Computer-Forensik
- Rechtswissenschaften Strafrecht Kriminologie, Strafverfolgung
Weitere Infos & Material
1. Why Python Forensics 2. creating a Python Forensics Workbench 3. Let's Write Our First Python Forensics App 4. Effective Forensic Searching and Indexing using Python 5. Evidence Carving with Python 6. Timeline Evidence with Python 7. Natural Language Processing of Evidence using Python 8. Examining Mobile Device Evidence with Python 9. Log File Analysis 10. Python Scripts for Network Investigation 11. Investigating the Cloud 12. Future Expansion