The societal, technological, and security impacts of advanced mobile communications networks cannot be understated. These networks impact billions of humans, even more devices, and play a role in nearly every human endeavor. 5G alone raises a range of social, technology, and security questions that include:
- How will 5G be used and what is its future impact on society?
- What are the implications of open and closed radio access networks (O-RAN, C-RAN, …)?
- How do we protect wireless cellular technology?
- Are there relevant risk management frameworks?
These questions span past, present, and future mobile communications networks. Gaining insight on these questions necessitates understanding both low-level technologies and high-level uses of advanced mobile communications networks. Obtaining the necessary facts and evidence leading to defensible courses-of-actions in the mobile communications domain requires analyzing data both within and across layers of the knowledge hierarchy in a way that is consistent with the deeply held privacy beliefs of our society, partners, and allies.
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Machine learning and artificial intelligence techniques play a key role in this domain. While these techniques can potentially reduce the time to action for critical missions, they are prone to a variety of adversarial attacks. For example, small perturbations of input features can cause dramatic changes to the output label from a machine learning classifier.
This course will explore the complex social/technological/security space of advanced mobile communications networks within the broader context of the machine learning and artificial intelligence revolution that is being applied to the network domain knowledge hierarchy. The course will introduce students to the world of advanced mobile communications networks and include, where possible, hands-on exercises with practical training.
Prerequisites: mathematics, computer science, and programming skills typical of college STEM degrees.
This course is by invitation only. Invitations are issued based on collaborations and not on an individual basis.
If you are currently enrolled, you can view the course content by visiting your Dashboard. To access your Dashboard, click on your username on the toolbar at the top of your screen and select it from the dropdown menu.
