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Tables of Contents for Investigative Data Mining for Security and Criminal Detection
Chapter/Section Title
Page #
Page Count
Introduction
xv
 
Precrime Data Mining
1
38
Behavioral Profiling
1
1
Rivers of Scraps
2
1
Data Mining
3
1
Investigative Data Warehousing
4
1
Link Analysis
5
1
Software Agents
6
2
Text Mining
8
1
Neural Networks
9
2
Machine Learning
11
3
Precrime
14
1
September 11, 2001
15
1
Criminal Analysis and Data Mining
15
4
Profiling via Pattern Recognition
19
3
Calibrating Crime
22
2
Clustering Burglars: A Case Study
24
13
The Future
37
1
Bibliography
38
1
Investigative Data Warehousing
39
36
Relevant Data
39
1
Data Testing
40
1
The Data Warehouse
40
2
Demographic Data
42
4
Real Estate and Auto Data
46
1
Credit Data
46
1
Criminal Data
47
8
Government Data
55
1
Internet Data
55
4
XML
59
2
Data Preparation
61
2
Interrogating the Data
63
1
Data Integration
64
1
Security and Privacy
65
1
ChoicePoint: A Case Study
66
2
Tools for Data Preparation
68
4
Standardizing Criminal Data
72
2
Bibliography
74
1
Link Analysis: Visualizing Associations
75
32
How Link Analysis Works
75
1
What Can Link Analysis Do?
75
1
What Is Link Analysis?
76
1
Using Link Analysis Networks
77
1
Fighting Wireless Fraud with Link Analysis: A Case Study
78
2
Types of Link Analysis
80
1
Combating Drug Trafficking in Florida with Link Analysis: A Case Study
81
1
Link Analysis Applications
82
2
Focusing on Money Laundering via Link Analysis: A Case Study
84
1
Link Analysis Limitations
85
3
Link Analysis Tools
88
16
Bibliography
104
3
Intelligent Agents: Software Detectives
107
18
What Can Agents Do?
107
1
What Is an Agent?
108
1
Agent Features
109
2
Why Are Agents Important?
111
1
Open Sources Agents
112
1
Secured Sources Agents
113
1
How Agents Work
113
1
How Agents Reason
114
2
Intelligent Agents
116
1
A Bio-Surveillance Agent: A Case Study
117
3
Data Mining Agents
120
1
Agents Tools
121
2
Bibliography
123
2
Text Mining: Clustering Concepts
125
34
What Is Text Mining?
125
1
How Does Text Mining Work?
126
1
Text Mining Applications
127
1
Searching for Clues in Aviation Crashes: A Case Study
128
2
Clustering News Stories: A Case Study
130
2
Text Mining for Deception
132
6
Text Mining Threats
138
3
Text Mining Tools
141
16
Bibliography
157
2
Neural Networks: Classifying Patterns
159
46
What Do Neural Networks Do?
159
1
What Is a Neural Network?
160
1
How Do Neural Networks Work?
161
1
Types of Network Architectures
162
1
Using Neural Networks
163
1
Why Use Neural Networks?
164
1
Attrasoft Facial Recognition Classifications System: A Demonstration
165
2
Chicago Internal Affairs Uses Neural Network: A Case Study
167
2
Clustering Border Smugglers with a SOM: A Demonstration
169
3
Neural Network Chromatogram Retrieval System: A Case Study
172
6
Neural Network Investigative Applications
178
1
Modus Operandi Modeling of Group Offending: A Case Study
179
16
False Positives
195
1
Neural Network Tools
196
8
Bibliography
204
1
Machine Learning: Developing Profiles
205
44
What Is Machine Learning?
205
1
How Machine Learning Works
206
1
Decision Trees
207
1
Rules Predicting Crime
208
2
Machine Learning at the Border: A Case Study
210
2
Extrapolating Military Data: A Case Study
212
1
Detecting Suspicious Government Financial Transactions: A Case Study
213
6
Machine-Learning Criminal Patterns
219
2
The Decision Tree Tools
221
8
The Rule-Extracting Tools
229
4
Machine-Learning Software Suites
233
15
Bibliography
248
1
NetFraud: A Case Study
249
26
Fraud Detection in Real Time
249
1
Fraud Migrates On-line
250
1
Credit-Card Fraud
250
1
The Fraud Profile
251
1
The Risk Scores
252
1
Transactional Data
253
1
Common-Sense Rules
253
1
Auction Fraud
254
2
NetFraud
256
1
Fraud-Detection Services
257
1
Building a Fraud-Detection System
258
1
Extracting Data Samples
259
1
Enhancing the Data
259
2
Assembling the Mining Tools
261
1
A View of Fraud
261
1
Clustering Fraud
262
2
Detecting Fraud
264
2
NetFraud in the United Kingdom: A Statistical Study
266
1
Machine-Learning and Fraud
267
4
The Fraud Ensemble
271
1
The Outsourcing Option
271
1
The Hybrid Solution
272
1
Bibliography
273
2
Criminal Patterns: Detection Techniques
275
26
Patterns and Outliers
275
1
Money As Data
276
1
Financial Crime MOs
277
2
Money Laundering
279
2
Insurance Crimes
281
6
Death Claims That Did Not Add Up: A Case Study
287
1
Telecommunications Crime MOs
288
3
Identity Crimes
291
2
A Data Mining Methodology for Detecting Crimes
293
3
Ensemble Mechanisms for Crime Detection
296
3
Bibliography
299
2
Intrusion Detection: Techniques and Systems
301
26
Cybercrimes
301
1
Intrusion MOs
302
7
Intrusion Patterns
309
1
Anomaly Detection
309
1
Misuse Detection
310
1
Intrusion Detection Systems
310
3
Data Mining for Intrusion Detection: A Case Study from the Mitre Corporation
313
5
Types of IDSs
318
1
Misuse IDSs
318
1
Anomaly IDSs
319
2
Multiple-Based IDSs
321
1
Data Mining IDSs
321
2
Advanced IDSs
323
1
Forensic Considerations
324
1
Early Warning Systems
325
1
Internet Resources
326
1
Bibliography
326
1
The Entity Validation System (EVS): A Conceptual Architecture
327
16
The Grid
327
1
GRASP
328
1
Access Versus Storage
328
1
The Virtual Federation
329
1
Web Services
330
1
The Software Glue
331
2
The Envisioned EVS
333
1
Needles in Moving Haystacks
334
2
Tracking Identities
336
1
The AI Apprentice
337
1
Incremental Composites
338
2
Machine Man
340
1
Bibliography
341
2
Mapping Crime: Clustering Case Work
343
36
Crime Maps
343
2
Interactive Crime GIS
345
1
Crime Clusters
346
2
Modeling the Behavior of Offenders Who Commit Serious Sexual Assaults: A Case Study
348
15
Decomposing Signatures Software
363
1
Computer Aided Tracking and Characterization of Homicides and Sexual Assaults (CATCH)
364
11
Forensic Data Mining
375
1
Alien Intelligence
376
2
Bibliography
378
1
A 1,000 Online Sources for the Investigative Data Miner
379
36
B Intrusion Detection Systems (IDS) Products, Services, Freeware, and Projects
415
4
C Intrusion Detection Glossary
419
12
D Investigative Data Mining Products and Services
431
4
Index
435