Investigative Data Mining for Security and Criminal Detection 

1 2 3 4 5

• 1. Table of Contents

• 2. BackCover

• 3. Investigative Data Mining for Security and Criminal Detection

• 4. Introduction

• 5. Chapter 1: Precrime Data Mining

  1.1 Behavioral Profiling

• 6. 1.2 Rivers of Scraps

  1.2 Rivers of Scraps

• 7. 1.3 Data Mining

  1.3 Data Mining

• 8. 1.4 Investigative Data Warehousing

  1.4 Investigative Data Warehousing

• 9. 1.5 Link Analysis

  1.5 Link Analysis

• 10. 1.6 Software Agents

  1.6 Software Agents

• 11. 1.7 Text Mining

  1.7 Text Mining

• 12. 1.8 Neural Networks

  1.8 Neural Networks

• 13. 1.9 Machine Learning

  1.9 Machine Learning

• 14. 1.10 Precrime

  1.10 Precrime

• 15. 1.11 September 11, 2001

  how pattern recognition is used to track criminals

• 16. 1.12 Criminal Analysis and Data Mining

  1.12 Criminal Analysis and Data Mining

• 17. 1.13 Profiling via Pattern Recognition

  1.13 Profiling via Pattern Recognition

• 18. 1.14 Calibrating Crime

  Data Mining (for dummies) how it can use to prevent a future attack on america like 9/11 bloodstain pattern analysis data mining

• 19. 1.15 Clustering Burglars: A Case Study

  1.15 Clustering Burglars: A Case Study 1.15.1 Introduction 1.15.2 The Application Task 1.15.3 Data Selection Cleaning and Coding 1.15.4 Application Construction 1.15.5 Findings 1.15.6 Validation Process 1.15.7 Discussion and Further Work 1.15.8 Conclusions

• 20. 1.16 The Future

  1.16 The Future

• 21. 1.17 Bibliography

  1.17 Bibliography

• 22. Chapter 2: Investigative Data Warehousing

  2.1 Relevant Data

• 23. 2.2 Data Testing

  2.2 Data Testing

• 24. 2.3 The Data Warehouse

  2.3 The Data Warehouse

• 25. 2.4 Demographic Data

  2.4 Demographic Data

• 26. 2.5 Real Estate and Auto Data

  2.5 Real Estate and Auto Data

• 27. 2.6 Credit Data

  2.6 Credit Data

• 28. 2.7 Criminal Data

  2.7 Criminal Data

• 29. 2.8 Government Data

  2.8 Government Data

• 30. 2.9 Internet Data

  2.9 Internet Data 2.9.1 Log Files 2.9.2 Cookies 2.9.3 Web Bugs 2.9.4 Internet Forms

• 31. 2.10 XML

  2.10 XML

• 32. 2.11 Data Preparation

  2.11 Data Preparation

• 33. 2.12 Interrogating the Data

  2.12 Interrogating the Data

• 34. 2.13 Data Integration

  2.13 Data Integration

• 35. 2.14 Security and Privacy

  2.14 Security and Privacy

• 36. 2.15 ChoicePoint: A Case Study

  2.15 ChoicePoint: A Case Study

• 37. 2.16 Tools for Data Preparation

  2.16 Tools for Data Preparation

• 38. 2.17 Standardizing Criminal Data

  2.17 Standardizing Criminal Data

• 39. 2.18 Bibliography

  2.18 Bibliography

• 40. Chapter 3: Link Analysis: Visualizing Associations

  3.1 How Link Analysis Works

• 41. 3.2 What Can Link Analysis Do?

  3.2 What Can Link Analysis Do?

• 42. 3.3 What Is Link Analysis?

  3.3 What Is Link Analysis?

• 43. 3.4 Using Link Analysis Networks

  3.4 Using Link Analysis Networks

• 44. 3.5 Fighting Wireless Fraud with Link Analysis: A Case Study

  3.5 Fighting Wireless Fraud with Link Analysis: A Case Study

• 45. 3.6 Types of Link Analysis

  3.6 Types of Link Analysis

• 46. 3.7 Combating Drug Trafficking in Florida with Link Analysis: A Case Study

  3.7 Combating Drug Trafficking in Florida with Link Analysis: A Case Study

• 47. 3.8 Link Analysis Applications

  3.8 Link Analysis Applications

• 48. 3.9 Focusing on Money Laundering via Link Analysis: A Case Study

  3.9 Focusing on Money Laundering via Link Analysis: A Case Study

• 49. 3.10 Link Analysis Limitations

  criminal detection social network machine learning data mining thesis

• 50. 3.11 Link Analysis Tools

  visually displaying criminal connections

1 2 3 4 5