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

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