Introduction to Information Security
This course introduces a variety of cyber security topics from a management, policy, and technology framework. Topics covered include; security of user-web interaction; safeguarding the Internet of Things; cyber-warfare; securing virtual, cloud, and mobile environments; and legal and ethical issues of security and privacy.
Randy Trzeciak holds a dual appointment between Heinz College and the CERT Program at the Software Engineering Institute. Randy is the Director of the Master of Science in Information Security Policy and Management program at CMU and instructs the core introductory course in the program. At CERT, Randy is the Technical Manager of the Enterprise Threat and Vulnerability Management Team and the Insider Threat Center
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Network Defenses
This course takes a hands-on approach, introducing students to network defenses to block, mitigate and detect cyber-attacks. Firewalls, intrusion detection systems (IDS), and network sniffers are some of the tools students will learn to deploy and configure in a live lab environment. Time will also be spent learning how to analyze data to make conclusions about the network that is being monitored and actively attacked.
Toby Meyer is a Senior Member of the Technical Staff at the Software Engineering Institute and a Team Lead in the CERT Cyber Workforce Development Directorate. He is a cybersecurity professional with extensive industry experience and serves as an adjunct in the Masters of Science Information Security Policy and Management (MSISPM) and Master of Science in Information Technology (MSIT) programs at CMU.
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Cybersecurity for Artificial Intelligence & Machine Learning
Advancements in artificial intelligence and machine learning have allowed for a surge in adoption of AI and ML solutions to address problems across numerous domains. With this rising reliance on AI and ML in many organizations, it is critical that such systems are protected from malicious activities. This course will discuss AI and ML cybersecurity issues, explore case studies of AI and ML cyber incidents, present AI and ML adversarial techniques, and demonstrate secure design approaches to protect AI and ML systems. With an emphasis on machine learning, the course will focus on secure machine learning systems development approaches and secure machine learning operations (MLOps).
Thomas P. Scanlon is a Senior Research Scientist and Technical Manager in the CERT Division of the Software Engineering Institute at Carnegie Mellon University. He leads the CERT Data Science technical program which incorporates artificial intelligence, machine learning, and statistical analyses to develop solutions for cybersecurity challenges. Scanlon’s research interests include generative AI, large language models (LLMs), cybersecurity, software engineering, threat modeling, human-computer interaction (HCI), and quantum computing.
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What's next?
Apply now to the IT Lab Summer Cybersecurity Fellowship.