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Machine Learning Forensics for Law Enforcement, Security, and Intelligence by Jesus Mena instant download

  • SKU: EBN-237389910
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Instant download (eBook) Machine Learning Forensics for Law Enforcement, Security, and Intelligence after payment.
Authors:Jesus Mena
Pages:updating ...
Year:2011
Publisher:Taylor & Francis Group
Language:english
File Size:4.49 MB
Format:epub
Categories: Ebooks

Product desciption

Machine Learning Forensics for Law Enforcement, Security, and Intelligence by Jesus Mena instant download

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 what they need to be prepared and stay ahead of the game. The book is a practical guide on how to conduct forensic investigations using self-organizing clustering map (SOM) neural networks, test 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. 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 preempting 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.
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