How are AI and machine learning integrated into Career Kickstart cybersecurity courses?

Cybersecurity professionals use machine learning to analyze large data sets (computer activity logs) and detect malicious cyber activity. Computers collect large amounts of data about users on their systems and all cyber adversaries leave traces through their actions. Humans could never sift through all the data to find and identify malicious activity, but computer algorithms can.
Generative AI is making some types of cyberattacks more effective, and it is lowering the barriers to entry for launching certain types of attacks. Adversaries can use generative AI to create deep fakes, voice cloning, scam emails, and malicious computer code (malware).
Generative AI can be used to attack AI models. Adversaries are actively seeking to exploit AI models themselves by poisoning the data being used to train the models, extracting information from the models’ training data, or injecting code or commands into models to change their behavior or output.
Cybersecurity 2: Cybersecurity Fundamentals covers the rise of automated tools and algorithms in detecting cyberattacks using tools such as IDS/IPS systems and SIEMs.
Cybersecurity 2: Cybersecurity Fundamentals includes a research project where students study an emerging technology that intersects with cybersecurity. AI and machine learning are among the potential topics that students can choose for this project.