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Machine Learning Forensik für Strafverfolgun
by Mena, Jesus | HC | LikeNew
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eBay-Artikelnr.:197390734809
Artikelmerkmale
- Artikelzustand
- Neuwertig
- Hinweise des Verkäufers
- Binding
- Hardcover
- Book Title
- Machine Learning Forensics for Law Enforcement, Security, and...
- Weight
- 1 lbs
- Product Group
- Book
- IsTextBook
- No
- ISBN
- 9781439860694
Über dieses Produkt
Product Identifiers
Publisher
Auerbach Publishers, Incorporated
ISBN-10
1439860696
ISBN-13
9781439860694
eBay Product ID (ePID)
99596510
Product Key Features
Number of Pages
349 Pages
Language
English
Publication Name
Machine Learning Forensics for Law Enforcement, Security, and Intelligence
Subject
Security / General, Forensic Science, Databases / Data Mining, Criminology, Information Technology
Publication Year
2011
Type
Textbook
Subject Area
Law, Computers, Social Science
Format
Hardcover
Dimensions
Item Height
0.9 in
Item Weight
22.4 Oz
Item Length
9.4 in
Item Width
6 in
Additional Product Features
Intended Audience
College Audience
LCCN
2011-026877
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
363.25028563
Table Of Content
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 Detection: On 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 From Extraction to Clustering Inductive Forensics: Clustering Incidents and Crimes Autonomous Forensics Self-Organizing Maps Clustering Software Commercial Clustering Software Free and Open-Source Clustering Software Mapping Incidents Clustering Crimes From Induction to Deduction Deductive Forensics: Anticipating Attacks and Precrime Artificial Intelligence and Machine Learning Decision Trees Decision Tree Techniques Rule Generators Decision Tree Tools Free and Shareware Decision Tree Tools Rule Generator Tools Free Rule Generator Tools The Streaming Analytical Forensic Processes Forensic Analysis of Streaming Behaviors Forensic Real-Time Modeling Deductive Forensics for Precrime 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 Four Key Steps in Dealing with Digital Evidence Searches for Associations: Discovering Links and Text Concepts Rules of Fraud: Conditions and Clues A Forensic Investigation Methodology Step One: Understand the Investigation Objective Step Two: Understand the Data Step Three: Data Preparation Strategy Step Four: Forensic Modeling Step Five: Investigation Evaluation Step Six: Detection Deployment Forensic Ensemble Techniques Stage One: Random Sampling Stage Two: Balance the Data Stage Three: Split the Data Stage Four: Rotate the Data Stage Five: Evaluate Multiple Models Stage Six: Create an Ensemble Model Stage Seven: Measure False Positives and Negatives Stage Eight: Deploy and Monitor Stage Nine: Anomaly Detection Fraud Detection Forensic Solutions Assembling an Evolving Fraud Detection Framework Cybersecurity Investigations: Self - Organizing and Evolving Analyses What Is Cybersecurity Forensics? Cybersecurity and Risk Machine Learning Forensics for Cybersecurity Deep Packet Inspection (DPI) Layer 7: Application Layer 6: Presentation Layer 5: Session Layer 4: Transport Layer 3: Network Layer 2: Data Link Layer 1: Physical Software Tools Using DPI Network Security Tools Combating Phishing Hostile Code The Foreign Threat The CNCI Initiative Details Forensic Investigator Toolkit Wireless Hacks Incident Response Check-Off Checklists Digital Fingerprint Corporate Counterintelligence: Litigation and Competitive Investigations Corporate Counterintelligence Ratio, Trending, and Anomaly Analyses E-Mail Investigations Legal Risk Assessment Audit Inventory of External Inputs to the Process Identify Assets and Threats List Risk Tolerance for Major Events List and Evaluate Existing Protection Mechanisms List and Assess Underprotected Assets and Unaddressed Threats Competitive Intelligence Investigations Triangulation Investigations Index
Synopsis
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.
LC Classification Number
HV8079.C65
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ThriftBooks
98,9% positive Bewertungen•19.7 Mio. Artikel verkauft
Angemeldet als gewerblicher Verkäufer
Verkäuferbewertungen (5'695'717)
- 3***w (172)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThe one star is for the condition of the book, not its contents. The cover of this paperback is on backwards and upside down. When the front cover is opened, the first page is actually the last page of the book.
- r***0 (214)- Bewertung vom Käufer.Letzter MonatBestätigter KaufGreat service, speedy delivery!
- d***d (19)- Bewertung vom Käufer.Letzter MonatBestätigter KaufThis product was packaged as new, but the code was scratched off, making it unusable. I have 0 issues with the seller. I have actually purchased from them before and would gladly purchase again. It was just the product.