Cybersecurity Informatics

This document provides details of a graduate-level course titled "Cybersecurity Informatics."

Course Description

This course introduces fundamental concepts, techniques, and tools in managing, analyzing, and interpreting data for cybersecurity informatics. The concepts and techniques include data description, modeling of user requirements and data properties, statistical summarization, making inferences from data, machine learning, and network analytics. Students will learn to use contemporary software tools to support the informatics process and research development. (Pre-requisites: graduate-level standing or instructor approval)

Course Developer

Wingyan Chung, Ph.D.
Associate Professor, Institute for Simulation and Training
Director, Cyber Intelligence Lab
University of Central Florida

Course Objectives

Upon successful completion of this course, students should be able to

Explain the challenges of managing data and applying informatics in the cybersecurity domain,
Model and describe data in the cybersecurity domain using statistical and analytical methods,
Make inferences and test hypotheses to support decision making to enhance cybersecurity,
Apply machine learning and network science approaches to prediction of cybersecurity phenomena, and
Use contemporary software tools to support management and analytics of cybersecurity data.

Course Documents

Course Schedule and Materials

Week	Topic	Assignments
0	Course Orientation	Syllabus, Expectations, Slides, Syllabus Quiz, Introduction Discussion
1	Understanding the cybersecurity landscape and the data environment	Discussion 1, Basic Commands in R
2	Data Summarization and Description in Cybersecurity Analysis	Problem Set 1
3	Developing Confidence Intervals for Cybersecurity Data	Problem Set 2
4	Interpreting Confidence Interval for Understanding Cyber Phenomena	Discussion 2
5	The Scientific Process of Detecting Cybersecurity Threats	Problem Set 3
6	Procedure and Tools for Interpreting Testing Results	Preparing for Midterm Exam
7	Mid-term Exam	-
8	Correlational Research in Cybersecurity	Discussion 3
9	Predicting Activities in Cybersecurity Events	Continue working on individual paper
10	Exploratory Study of Cyber Phenomena	Discussion 4
11	Clustering Cybersecurity Cases and Data	Problem Set 4
12	Profiling and Categorizing Intelligence Factors	BizPro Presentation
13	Classifying Cybersecurity Incidents and Threats	Vector Semantics and Applications to Cybersecurity, Discussion 5
14	Understanding Networks of Actors in Cybersecurity Incidents	Problem Set 5
15	Modeling Networks for Community Analyses	Preparing for Final Exam
16	Final Exam	Individual Paper

Resources

Acknowledgments

Grant Award from Intel Corporation's Security Curriculum Program.

Cyber Intelligence Lab | Institute for Simulation and Training | University of Central Florida
3100 Technology Parkway, Orlando, Florida 32826, U.S.A. | Tel.: +1 (407) 882-1300 | Fax: +1 (407) 882-1335