Table of contents for Data mining for intelligence, fraud & criminal detection : advanced analytics & information sharing technologies / Christopher Westphal.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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Table of Contents
Table of Contents	2
Foreword	8
Dedication	14
Acknowledgements	14
Biography	18
Section 1 Introduction	1
Chapter 1 - Overview	1
Sharing Data	3
Connect the Dots	7
Analytical Versus Referential Data	17
Information Sharing	26
Conclusion	33
Chapter 2 - The Quality of Data	1
Value Errors	3
Missing Data and Bad Structures	8
Unique Addresses	12
Distinct Phone Numbers	13
Individual ID Numbers	16
Anomalous Accounts	16
One of a Kind Transactions	17
Original Organizations	18
Perspicuous People	20
Entity Resolution	22
Anonymous Resolution	35
Conclusion	41
Chapter 3 - What are Patterns?	1
Which Pattern Is More Important?	7
Do These Patterns Make Sense?	16
Is This a Reliable Pattern?	20
Is This an Actionable Pattern?	23
Which Pattern is More Valuable?	25
What Does this Pattern Show?	28
Who is the Most Important Person?	36
Conclusion	39
Section 2 Introduction	1
Chapter 4 - Border Protection	1
I-94- Arrival/Departure Records	1
Land Border Targeting	8
Cluster by Hour of the Day (HOD)	24
Cluster by Day of the Week (DOW)	26
Figure 4.18. Date Grid Showing Crossing Behavior by Day/Week	27
Cluster by Date	27
Cluster by Port of Entry (POE)	28
Clusters by Lane	29
Cluster by Inspector	29
Cluster by City/State	30
Cluster by VIN	30
Putting It Together	31
Conclusion	32
Chapter 5 - Money Laundering and Financial Crimes	1
Suspicious Activity Reports	19
Structuring Transactions	23
Bust Out Schemes	27
A Consumer Bust-Out Scheme	32
Busting and Kiting	34
Identity Fraud	36
Large Connections	38
Attorneys and Law Firms	43
Cheap Motels	45
Location, Location, Location	47
Individual Taxpayer Identification Number	52
SAR Versus STR	55
Timing is Everything	58
A Final Note	64
Conclusion	72
Chapter 6 - Money Service Businesses	1
Why Wire Remitters?	2
Steps of a Wire Remittance	4
Structure of a Wire Transfer	6
Combating Human Smuggling	13
The Smuggling Process	17
Changing the Rules	26
Seizing Assets	29
Corridor States	32
Drug Dealers	37
Suspicious Activity Reports	38
Elderly Abuse Pattern	41
Ornery Old Man	43
Other MSB Patterns	45
Multiple Locations	45
Minimal Overlaps	46
Official Deposits	48
Heavenly Offerings	50
Dirty Dancing	52
Conclusion	53
Chapter 7 - Fraud Analytics	1
Warranty Fraud Anecdotes	4
Automobile Warranties	5
Hurricane Katrina	12
Corporate Frauds	20
Employees as Vendors	21
Vendors as Vendors	23
Corporate Expenses	26
Duplicate Payments	29
Human Resources	32
Gift Card Fraud	35
Additional Examples	39
Pharmaceutical	40
Phishing / Click Fraud	41
Tax Evasion	42
Conclusion	55
Section 3 Introduction	1
Chapter 8 - Information Sharing Protocols	1
Global Justice XML Data Model (Global JXDM)	3
Data Dictionary	4
Data Model	7
Component Reuse Repository	9
National Information Exchange Model	12
28 CFR Part 23	15
Conclusion	24
Chapter 9 - Information Sharing Systems	1
Automated Regional Justice Information System ARJIS	7
Comprehensive Regional Information Management Exchange System (CRIMES)	13
Factual Analysis Criminal Threat Solution (FACTS) System	15
Florida Information Network for Data Exchange and Retrieval (FINDER)	17
Ohio Local Law Enforcement Information Sharing Network (OLLEISN),	19
Law Enforcement Information Exchange (LInX)	21
OneDOJ , R-DEx, N-DEx	23
Law Enforcement Online (LEO)	27
Joint Regional Information Exchange System (JRIES)	27
Joint Terrorism Task Force (JTTF)	29
State-Level Fusion Centers	32
High Intensity Drug Trafficking Area (HIDTA)	39
High Intensity Financial Crime Areas (HIFCA)	45
Regional Information Sharing Systems (RISS)	49
Conclusion	52
Summary	1

Library of Congress Subject Headings for this publication:

Law enforcement -- United States.
Data mining -- United States.