Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive and instructive tools, techniques, and technologies to arm professionals with the tools they need to be prepared and stay ahead of the game.
Step-by-step instructions
The book is a practical guide on how to conduct forensic investigations using self-organizing clustering map (SOM) neural networks, text extraction, and rule generating software to "interrogate the evidence." This powerful data is indispensable for fraud detection, cybersecurity, competitive counterintelligence, and corporate and litigation investigations. The book also provides step-by-step instructions on how to construct adaptive criminal and fraud detection systems for organizations.
Prediction is the key
Internet activity, email, and wireless communications can be captured, modeled, and deployed in order to anticipate potential cyber attacks and other types of crimes. The successful prediction of human reactions and server actions by quantifying their behaviors is invaluable for pre-empting criminal activity. This volume assists chief information officers, law enforcement personnel, legal and IT professionals, investigators, and competitive intelligence analysts in the strategic planning needed to recognize the patterns of criminal activities in order to predict when and where crimes and intrusions are likely to take place.
Contents
What Is Machine Learning Forensics?
Definition
Digital Maps and Models: Strategies and Technologies
Extractive Forensics: Link Analysis and Text Mining
Inductive Forensics: Clustering Incidents and Crimes
Deductive Forensics: Anticipating Attacks and Precrime
Fraud Deten the Web, Wireless, and in Real Time
Cybersecurity Investigations: Self-Organizing and Evolving Analyses
Corporate Counterintelligence: Litigation and Competitive Investigations
A Machine Learning Forensic Worksheet
Digital Investigative Maps and Models: Strategies and Techniques
Forensic Strategies
Decompose the Data
Criminal Data Sets, Reports, and Networks
Real Estate, Auto, and Credit Data Sets
Psychographic and Demographic Data Sets
Internet Data Sets
Deep Packet Inspection (DPI)
Designing a Forensic Framework
Tracking Mechanisms
Assembling Data Streams
Forensic Techniques
Investigative Maps
Investigative Models
Extractive Forensics: Link Analysis and Text Mining
Data Extraction
Link Analysis
Link Analysis Tools
Text Mining
Text Mining Tools
Online Text Mining Analytics Tools
Commercial Text Mining Analytics Software
...