Excel Applications for Accounting Principles or Investigative Data Mining for Security and Criminal Detection

Excel? Applications for Accounting Principles

Author: Gaylord N Smith

The text introduces students to the power of spreadsheets. It contains over 50 spreadsheet problems that reinforce principles of accounting concepts. The problems incorporate formula development and model building skills that may be used in a variety of accounting applications. Emphasis is placed on what if analysis.

See also: Angariação de fundos de Modificação Social

Investigative Data Mining for Security and Criminal Detection

Author: Jesus Mena

Investigative Data Mining for Security and Criminal Detection is the first book to outline how data mining technologies can be used to combat crime in the 21st century. It introduces security managers, law enforcement investigators, counter-intelligence agents, fraud specialists, and information security analysts to the latest data mining techniques and shows how they can be used as investigative tools. Readers will learn how to search public and private databases and networks to flag potential security threats and root out criminal activities even before they occur.

The groundbreaking book reviews the latest data mining technologies including intelligent agents, link analysis, text mining, decision trees, self-organizing maps, machine learning, and neural networks. Using clear, understandable language, it explains the application of these technologies in such areas as computer and network security, fraud prevention, law enforcement, and national defense. International case studies throughout the book further illustrate how these technologies can be used to aid in crime prevention.

Investigative Data Mining for Security and Criminal Detection will also serve as an indispensable resource for software developers and vendors as they design new products for the law enforcement and intelligence communities.


Key Features:

* Covers cutting-edge data mining technologies available to use in evidence gathering and collection

* Includes numerous case studies, diagrams, and screen captures to illustrate real-world applications of data mining

* Easy-to-read format illustrates current and future data mining uses inpreventative law enforcement, criminal profiling, counter-terrorist initiatives, and forensic science

* Introduces cutting-edge technologies in evidence gathering and collection, using clear non-technical language
* Illustrates current and future applications of data mining tools in preventative law enforcement, homeland security, and other areas of crime detection and prevention
* Shows how to construct predictive models for detecting criminal activity and for behavioral profiling of perpetrators
* Features numerous Web links, vendor resources, case studies, and screen captures illustrating the use of artificial intelligence (AI) technologies

Table of Contents:

	Introduction
1	Precrime Data Mining	1
2	Investigative Data Warehousing	39
3	Link Analysis: Visualizing Associations	75
4	Intelligent Agents: Software Detectives	107
5	Text Mining: Clustering Concepts	125
6	Neural Networks: Classifying Patterns	159
7	Machine Learning: Developing Profiles	205
8	NetFraud: A Case Study	249
9	Criminal Patterns: Detection Techniques	275
10	Intrusion Detection: Techniques and Systems	301
11	The Entity Validation System (EVS): A Conceptual Architecture	327
12	Mapping Crime: Clustering Case Work	343
A	1,000 Online Sources for the Investigative Data Miner	379
B	Intrusion Detection Systems (IDS) Products, Services, Freeware, and Projects	415
C	Intrusion Detection Glossary	419
D	Investigative Data Mining Products and Services	431
	Index	435