Intelligence Analysis (IA)

Cyber intelligence (CI) can be viewed from Sun Tzu's (Chinese Military General) perspective of knowing yourself, understanding your enemies and exploiting information for decision making. Students use cyber threat frameworks to develop common vocabulary for technical and non-technical discussions of cyber security with management and technical staff. They identify and apply cyber analytical methodologies (e.g., NIST framework, CI tradecraft, SWOT, tiered threat matrix) to the organization and identify as well as categorize its cyber threat environment. Using the analysis, students design data gathering plans, harvest open source information, analyze diverse data and conduct basic technical as well as strategic analysis of cyber threats and adversaries. Using analytical approaches, students focus on behavioral, cultural and geopolitical aspects of cyber security.

Using case studies, this course provides an overview of cyber methodologies based on industry best practices for analyzing cyber threats, assessing an organization's cyber posture and conducting proactive analysis of cyber adversaries to support network defense and decision making. By applying these cyber methodologies, students will have a systematic, threat-driven approach for dealing with the complexity, uncertainty and ambiguous cyber domain. With the increasing volume of diverse, ambiguous and contradictory data sources, students must systematically consider a range of alternative hypotheses and outcomes. These methodologies, developed in the business and intelligence communities, will allow students to explore problems from different perspectives. Methodologies are organized into categories based on their purposes: diagnostic, descriptive, predictive and prescriptive.

This course enables students to develop broad technical competencies of the current and future technology applications associated with networking, cyber security, databases and mobility. It supports cyber intelligence courses which involve information gathering and analysis of open source information about cyber threats and adversaries to support managerial decision making. It provides networking foundation for understanding the internetwork environment and functioning as part of a cyber security team. Using lab-based exercises and case studies, the course emphasizes internetworking, security vulnerabilities, ethical cyber security issues and the hacker's lifecycle including major components: reconnaissance, scanning and probing, exploitation and post-exploitation.

This course provides an introduction to major ethical, legal and policy issues as well as privacy challenges (e.g., consumers losing control over how their personal information is collected and used) in responding to cyber threat landscape. The course explores the relationship of the issues and provides the opportunity for vigorous discussion and exploration of them. It uses case studies, demonstrations and guest speakers to explore ethics and the federal, state and local legislations and how they influence cybersecurity. It provides the foundation for comparing issues associated with ethics in deciding on a course of action, legislative approaches (e.g., federal and international) and policies. Particular focus is given to ethical and privacy challenges as well as the need for enhanced federal and international collaboration and information sharing.

This course introduces students to the basic concepts of big data analytics with applications in social media and emphasizes social, legal and ethical issues. Social media is big data that can help an organization to connect with their client base, increase productivity and improve proactive decision making. The course covers characteristics, transparency, ethical/legal issues and methodologies such as diagnostic, descriptive, predictive and prescriptive social media analytics. The course provides the foundation for students to become sensitive to their biases, conducts social media analytics at different levels (e.g., diagnostic and predictive) and generates alternative analysis to support data-driven decision making.

This course involves conceptualization, identification and analysis of an engaging topic in social, technical or behavioral issues associated with cyber threats and adversaries. It provides an opportunity to conduct analysis of a contemporary topic and explore cyber threats in a specific domain (e.g., finance, education, national security, healthcare). This involves working with domain experts to create a cyber intelligence project that integrates concepts covered in this program. The project demonstrates competencies in connecting the dots, conducting open source analysis, thinking critically and trying to identify adversaries' actions based on their motivations, capabilities, activities and geopolitical interests.

This course takes a holistic look at financial crimes from a definitional standpoint according to type, the laws in place that govern monetary transactions and property crimes in the United States; global agreements and cooperation in combating financial theft in cyber space; and a thorough examination of the domestic and international law enforcement agencies who investigate and prosecute criminals.