Machine learning forensics for law enforcement, security, and intelligence
Author(s)
Bibliographic Information
Machine learning forensics for law enforcement, security, and intelligence
CRC Press, c2011
- : hardback
Available at / 1 libraries
-
No Libraries matched.
- Remove all filters.
Search this Book/Journal
Note
Includes index
Description and Table of Contents
Description
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.
Table of Contents
What Is Machine Learning Forensics? Digital Investigative Maps and Models: Strategies and Techniques. Extractive Forensics: Link Analysis and Text Mining. Inductive Forensics: Clustering Incidents and Crimes. Deductive Forensics: Anticipating Attacks and Precrime. Fraud Detection: On the Web, Wireless, and in Real Time. Cybersecurity Investigations: Self - Organizing and Evolving Analyses. Corporate Counterintelligence: Litigation and Competitive Investigations. Index.
by "Nielsen BookData"