Courses

This studio course teaches four basic hands-on cyber-defense skills: configuring a firewall, implementing a host-based intrusion detection software tool, using the Metasploit tool to do penetration testing, and implementing a network intrusion detection tool.

This course provides the student with the background, experience and perspective that is required to document organizational preparation for cyber incidents, document cyber incident impact and resolution, document response strategies, as well as integrate business continuity planning into the organization.

This studio course teaches fundamental data-driven cybersecurity analytics skills using programming skills acquired in earlier courses.

Malware Analytics is an intermediate course required for students who are majoring in Cybersecurity Analytics and Operations. It is a three-credit hands-on course that teaches principles and practice of malware detection, analysis, and defense.

Cybersecurity Capstone is an advanced, culminating course for students who are majoring in Cybersecurity. This course provides the student with a practical exercise, designed by the instructor.

Introduction to the concept of databases, including the storage, manipulation, evaluation, and display of data, and related issues.

Introduction to digital network topologies, transmission media, signal modulation, digital packet switching and routing, systems integration, communications management, and security.

Introduction to formal languages, mathematical logic, and discrete mathematics, with applications to information sciences and technology.

Legal environment of information technology, constitutional/political issues, intellectual property, management, e-commerce, privacy, access, computer contracting, cyberspace regulation.

Fundamental issues and concepts of network security, network security technologies and protocols, and emerging technologies in network security.

Fundamental issues and concepts of computer forensics; aspects of computer and cybercrime; methods to uncover, protect, exploit, and document digital evidence; tools, techniques, and procedures to perform computer and cybercrime investigation.

Contemporary security issues; security management processes, architecture, and models; risk analysis and management; security planning, analysis, and safeguards; security policies development and administration; contingency planning, incidence handling, and response; and security standards and certification processes.

Supervised off-campus, nongroup instruction including field experiences, practica, or internships. Written and oral critique of activity required.

This introductory course spans areas of security, risk, and analysis covering contexts in government agencies and business organizations.

Provides overview of nature, scope, and seriousness of threats to security as a result of terrorism and crime.

Provides an understanding of the overview of information security including security architecture, access control, and internet secure applications.

Provides an overview of decision theoretical and analytical concepts and tools in the security risk analysis field.

Assessment and mitigation of security vulnerabilities for people, organizations, industry sectors, and the nation.

This course emphasizes how to summarize data using descriptive statistics, how to make data-driven decisions using inferential statistics, and how to critically evaluate data presented in the media, all within the context of security, risk, and analysis. This is both a theory and application course. Students will learn about statistical theories, such as regression, and chi-square analyses, and apply their knowledge of these theories by analyzing and interpreting data using a statistical software package.

This is an introductory university-level course in computer systems literacy. The history, architecture and operation of computing systems and underlying computing theory are covered.

Descriptive Statistics, frequency distributions, probability and normal distributions, statistical inference, linear regression, and correlation.

A first course in concepts and skills for application development.

Intermediate application development including algorithms, data structures, and object-oriented concepts.