| Item type | Current library | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Book Closed Access
|
Engineering Library | 363.250285631 MEN 1 (Browse shelf(Opens below)) | 1 | Available | BUML24010274 |
CONTENTS
Chapter 1. What is machine learning forensics?
Definition
Digital maps and models: strategies and technologies
Extractive forensics: Analysis and text mining
etc...
Chapter 2. Digital investigative maps and models: strategies and techniques
Forensic strategies
Decompose the data
Criminal data sets, reports, and networks
etc...
Chapter 3. Extractive forensics: Link analysis and text mining
Data extraction
Link analysis
Link analysis tools
etc...
Chapter 4. Inductive forensics: clustering incidents and crimes
Autonomous forensics
Self-organizing maps
Clustering software
etc...
Chapter 5. Deductive forensics: anticipating attacks and precrime
Artificial intelligence machine learning
Decision trees
Decision tree techniques
etc...
Chapter 6. Fraud detection: on the web, wireless, and in real time
Definition and techniques: where, who, and how
The interviews: the owners, victims, and suspects
The scene of the crime: search for digital evidence
etc...
Chapter 7. Cybersecurity investigations: self-organizing and evolving analysis
What is cybersecurity forensics?
Cybersecurity and risk
Machine learning forensics for cybersecurity
etc..
Chapter 8. Corporate counterintelligence: litigation and competitive investigation
Corporate counterintelligence
Ratio, trending, and anomaly analysis
E-mail investigations
etc...
Includes index P. 307-337
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