Professional Science Masters Degree in Cyber Security

Time to Degree

The Professional Science Masters Degree program can be completed at different paces to accommodate your schedule. Check the sample schedules page for more information about available program schedules.

Professional Outcomes

The PSM in Cyber Security is both an educational degree and job skill preparation. Students are guided through academic study to actionable skills that are used in the cyber security industry. The National Initiative for Cybersecurity Education (NICE) has produced a Cybersecurity Workforce Framework to help employers build their workforce. As part of this initiative, educational institutions are encouraged to map programs to the framework’s knowledge, skills and abilities. The Professional Science Masters Degree in Cyber Security maps to the following NICE Framework categories:

• Protection and Defense
• Investigation

CAE CyberAI Designation

URI’s PSM curriculum now addresses the National Security Agency’s CAE CyberAI Knowledge Unit framework, which defines workforce competencies for professionals working at the intersection of AI and cybersecurity. The AI Track satisfies most Core Knowledge Units in both the SecureAI program of study (securing AI systems) and the AICyber program of study (using AI in cybersecurity practice), giving graduates a great start on a credential pathway recognized by federal agencies and defense employers.

Educational Learning Outcomes

1. Protect and defend computer systems and networks from cybersecurity attacks.
   1.1 Characterize privacy, legal and ethical issues of information security.
   1.2. Identify vulnerabilities critical to the information assets of an organization.
   1.3. Define the security controls sufficient to provide a required level of confidentiality, integrity, and availability in an organization’s computer systems and networks.
2. Diagnose and investigate cybersecurity events or crimes related to computer systems and digital evidence.
   2.1. Diagnose attacks on an organization’s computer systems and networks.
   2.2. Propose solutions including development, modification and execution of incident response plans.
   2.3. Apply critical thinking and problem-solving skills to detect current and future attacks on an organization’s computer systems and networks.
3. Effectively communicate in a professional setting to address information security issues.
   3.1. Communication orally and in writing, proposed information security solutions to technical and non-technical decision-makers.
   3.2. Apply business principles to analyze and interpret data for planning, decision-making, and problem solving in an information security environment.
4. For the AI Track:  Apply artificial intelligence methods to cybersecurity challenges and defend AI systems against adversarial threats.
   4.1. Implement machine learning-based approaches to threat detection, log analysis, and anomaly identification.
   4.2. Evaluate vulnerabilities in AI/ML systems and apply mitigation strategies against adversarial attacks, data poisoning, and model manipulation.
   4.3. Assess AI governance, risk, and compliance considerations including NIST AI RMF, MITRE ATLAS, and responsible AI practices.

Curriculum

The degree requires 36 credits which consists of nine four-credit courses. This curriculum includes an experiential learning course, commonly satisfied by an internship or at your current employer. This capstone course will provide practical experience in the field of cybersecurity.

The degree requires five specific core courses. Students are free to choose four more courses that focus on areas of their own interest.

Choose Your Path: Standard Track or AI Track

The PSM in Cybersecurity is offered in two tracks, both consisting of nine four-credit courses (36 credits). Standard Track:  The foundational cybersecurity curriculum covering network security, incident response, penetration testing, forensics, and professional practice. AI Track (NEW):  The same rigorous cybersecurity foundation, with two specialized AI courses replacing two electives. Students gain expertise in securing machine learning systems and applying AI tools to cybersecurity operations.

Background Material

Fundamentals for Cyber Security is a self-paced program for enrolled students in basic technology concepts, available for students coming from less technical backgrounds. This material is provided the summer before the program begins.

Core Courses

Students take all five of the core courses. These courses guide students into the field by introducing concepts at a predictable and well-paced rate.

CSF 430 – Introduction to Information Assurance
CSF 432 – Introduction to Network and Systems Security
CSF 534 – Advanced Topics in Network and Systems Security
CSF 580 – Professional Skills for Cyber Security
CSF 590 – Cyber Security Internship

AI Track Concentration Courses 

[NEW] Students in the AI Track choose these two courses in place of two standard electives:

CSF 592 – Machine Learning Security An in-depth exploration of the security of machine learning systems, focusing on vulnerabilities of modern classifiers to adversarial attacks and defenses. Topics include PyTorch programming for ML, white-box and black-box evasion attacks (FGSM, PGD, C&W, APGD), and defenses such as gradient masking, model ensembles, autoencoders, and adversarial training. Satisfies NSA CAE SecureAI Core Knowledge Units.

CSF 470 – Applied AI for Cybersecurity Applies supervised, unsupervised, and reinforcement learning to cybersecurity problems including log analysis, static code analysis, deobfuscation, threat detection, and anomaly detection. Students also examine how threat actors leverage AI and evaluate ethical, privacy, and adversarial implications. Prerequisite: CSF 432. Satisfies NSA CAE AICyber Core Knowledge Units.

Industry Certification Alignment:  CompTIA SecAI+

URI’s AI Track coursework prepares students, with additional self-study,  to sit for the CompTIA SecAI+ certification, launched in 2026. SecAI+ is the cybersecurity industry’s first credential validating expertise in both securing AI systems and leveraging AI tools for cyber defense. Exam domains include AI Concepts (17%), Securing AI Systems (40%), AI-Assisted Security (24%), and AI Governance, Risk & Compliance (19%).

Concentration Course Electives

Students choose four concentration courses. These courses target specific concepts and practices within the wide field of cybersecurity technology. A complete list of courses can be found by browsing the course descriptions page.

CSF 410 – Digital Forensics I
CSF 524 – Advanced Incident Response
CSF 536 – Advanced Intrusion Detection and Defense
CSF 538 – Penetration Testing
CSF 540 – Intro to Malware Analysis
CSF 560 – Cyber Threat Intelligence
All other 500-level CSF courses