Python Forensics: A Workbench for Inventing and Sharing Digital Forensic Technology
Autor Chet Hosmeren Limba Engleză Paperback – 31 oct 2024
- Provides hands-on tools, code samples, and detailed instruction and documentation that can be put to use immediately
- Discusses how to create a Python forensics workbench
- Covers effective forensic searching and indexing using Python
- Shows how to use Python to examine mobile device operating systems
- Delves into extensive machine learning integration with the Python ecosystem, integration of Python with Generative Pre Trainer-Transformers such as GPT-3, ChatGPT, and other new and emerging applications of Python to digital forensics
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (2) | 403.28 lei 2-4 săpt. | |
ELSEVIER SCIENCE – 31 oct 2024 | 403.28 lei 2-4 săpt. | |
ELSEVIER SCIENCE – 8 iun 2014 | 463.47 lei 6-8 săpt. |
Preț: 403.28 lei
Preț vechi: 504.11 lei
-20% Nou
Puncte Express: 605
Preț estimativ în valută:
77.17€ • 81.37$ • 64.25£
77.17€ • 81.37$ • 64.25£
Carte disponibilă
Livrare economică 14-28 decembrie
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780443222337
ISBN-10: 0443222339
Pagini: 400
Dimensiuni: 191 x 235 mm
Ediția:2
Editura: ELSEVIER SCIENCE
ISBN-10: 0443222339
Pagini: 400
Dimensiuni: 191 x 235 mm
Ediția:2
Editura: ELSEVIER SCIENCE
Cuprins
1. The evolution of Python for investigative acquisition and analysis
2. Integrating advanced 3rd Party Libraries for Machine Learning, Natural Language Processing, eDiscovery, GPT, social media and malware investigations
3. Integrating Python with forensics and cyber security platforms
4. Forensics Searching using regular expressions, YARA rules, targeting static and dynamic environments including Web and Social Platforms
5. Analysis of photographic images for the identification of fake photos, deep fake videos/audio, and data hiding methods
6. Extracting and analyzing time of static and dynamic evidence sources including social platforms
7. Extracting meaning and sentiment from news stories, tweets, and other social media communications
8. Performing packet capture and deep packet analysis
9. Gathering open-source intelligence from social platforms and eDiscovery applications
10. Python Forensics in the Cloud
11. Integrating Python with GPT-3 and ChatGPT
12. Applying Python and Machine Learning within forensic investigations. Identifying fake news, Spear Phishing, GPT generated text, echo chambers, and propaganda
13. What is ahead for Python and Forensics
2. Integrating advanced 3rd Party Libraries for Machine Learning, Natural Language Processing, eDiscovery, GPT, social media and malware investigations
3. Integrating Python with forensics and cyber security platforms
4. Forensics Searching using regular expressions, YARA rules, targeting static and dynamic environments including Web and Social Platforms
5. Analysis of photographic images for the identification of fake photos, deep fake videos/audio, and data hiding methods
6. Extracting and analyzing time of static and dynamic evidence sources including social platforms
7. Extracting meaning and sentiment from news stories, tweets, and other social media communications
8. Performing packet capture and deep packet analysis
9. Gathering open-source intelligence from social platforms and eDiscovery applications
10. Python Forensics in the Cloud
11. Integrating Python with GPT-3 and ChatGPT
12. Applying Python and Machine Learning within forensic investigations. Identifying fake news, Spear Phishing, GPT generated text, echo chambers, and propaganda
13. What is ahead for Python and Forensics
Recenzii
"Covering a panoply of techniques from search to network forensics, reading this book will expand the reader’s understanding of both forensics and the Python libraries." --Computing Reviews
"Overall, the book is well laid out. The first few chapters cover some important forensic challenges. The code is easy to follow and well commented." --Help Net Security
"Overall, the book is well laid out. The first few chapters cover some important forensic challenges. The code is easy to follow and well commented." --Help Net Security