SUMMARY
The course will discuss data mining technologies in detail and then examine their applications to counter-terrorism. In particular, we will discuss how data mining could help with national security problems such as detecting and preventing terrorism, cyber security problems such as detecting malicious intrusions and other topics such as insider threat analysis and handling real-time threats such as credit card fraud detection.

OBJECTIVE
The course will be divided into four parts: Part I will provide an overview of the supporting technologies for data mining such as database management, data warehousing, statistical reasoning and machine learning. Part II will give an introduction to data mining and discuss the outcomes, methodologies and techniques as well as provide an overview of the tools applications and directions. Part III will describe data mining techniques in detail. The techniques covered will include market basket analysis, decision trees, and link analysis, nearest neighbor, neural networks and genetic algorithms. Part IV will examine the application of data mining for counter-terrorism.

WHO SHOULD ATTEND
This course will be useful for anyone interested in learning about data mining. It will provide fair amount of details of the technologies and the techniques. Then for each technique we will examine its application for counter-terrorism. It will also be useful for those developing data mining techniques as well as managers of data mining projects. Finally, it will be extremely useful for counter-terrorism experts to learn about data mining.

COURSE OUTLINE: Data Mining Technologies and Applications in Business Intelligence and National Security

Introduction to the Course

Supporting Technologies for Data Mining

• Database Management
• Data Warehousing
• Statistical Reasoning
• Machine Learning
• Other Technologies: e.g., Visualization, Decision Support, Knowledge Management, Parallel Processing

Introduction to Data Mining

• Data Mining Overview
• Data Mining Outcomes, Methodologies and Techniques
• Data Mining Tools
• Data Mining Challenges and Directions: e.g. mining multimedia databases, Web mining
• Data Mining Applications: e.g. Marketing and Sales, Bioinformatics, etc.

Data Mining Techniques

• Market Basket Analysis
• Link Analysis
• Decision Trees
• Nearest Neighbor
• Neural Networks
• Genetic Algorithms

Data Mining for Business Intelligence

• Data Mining for E-Business Applications
• Data Mining for Customer Relationship Management
• Data Mining for Knowledge Management

Data Mining for Security Applications

• Data Mining for National Security and Counter-terrorism
• Data Mining for Law Enforcement
• Data Mining for Cyber Security Applications

Prototypes and Experimental Systems

• Surveillance and Suspicious Event Detection
• Geospatial Data Mining
• Privacy Preserving Data Mining
• Social Network Analysis
• Assured Information Sharing
• Automated Face Detection
• Web Analytics
• Intrusion Detection

Conclusion of the Course

Reference Books

Web Data Mining Technologies and Their Applications in Business Intelligence and Counter-terrorism

Author: Dr. Bhavani Thuraisingham
Publisher: CRC Press
Date: June 2003

Database and Applications Security: Integrating Data Management and Information Security

Author: Dr. Bhavani Thuraisingham
Publisher: CRC Press
Date: March 2005

Lecturer
Dr. Bhavani Thuraisingham

Dr. Bhavani Thuraisingham has recently joined University of Texas, Dallas as a Professor of Computer Science and Director of the Cyber Security Research Center at the Erik Jonsson School of Engineering. She is a Fellow of the IEEE (Institute for Electrical and Electronics Engineers) and AAAS (American Association for the Advancement of Science). She received IEEE Computer Society’s prestigious 1997 Technical Achievement Award for “outstanding and innovative contributions to secure data management”.

Dr. Thuraisingham’s research in information security and information management has resulted in over 70 journal articles, over 200 refereed conference papers, and three US patents. She is the author of seven books in data management, data mining and data security including one on data mining for counter-terrorism. She has given over 30 keynote presentations at various research conferences and has also given invited talks at the White House Office of Science and Technology Policy and at the United Nations on Data Mining for counter-terrorism.  She serves (or has served) on editorial boards of top research journals.

Prior to joining UTD, Dr. Thuraisingham was an IPA (Intergovernmental Personnel Act) at the National Science Foundation from the MITRE Corporation. At NSF she established the Data and Applications Security Program and co-founded the Cyber Trust theme and was involved in inter-agency activities in data mining for counter-terrorism. She was at MITRE between January 1989 and June 2005 and has worked in MITRE's Information Security Center and was later a department head in Data and Information Management as well as Chief Scientist in Data Management. She has served as an expert consultant in information security and data management to the Department of Defense, the Department of Treasury and the Intelligence Community for over 10 years. Thuraisingham’s industry experience includes six years of research and development at Control Data Corporation and Honeywell Inc.

Dr Thuraisingham is the Founding President of “Bhavani Security Consulting” a company providing services in consulting and training in Cyber Security and Information Technology. She serves as an expert software consultant to the Treasury on corporate research credit issues and advises Treasury counsel on software related court cases. She is also interested in the developments, challenges and issues associated with Intellectual Property management and writes articles on this topic as well as conducts technology strategy surveys and forecasting for Corporations.

Dr. Thuraisingham was educated in the United Kingdom both at the University of Bristol and at the University of Wales.