Internet-of-Things Security and Privacy: A Data-Driven Perspective

Catalog description

Smart home IoT (Internet-of-Things) devices are gaining popularity in average consumer homes. These “smart” devices, such as cameras, plugs, TVs, dishwashers, etc, are also known to pose various security and privacy threats (e.g., your Alexa listening to you), but the opaque nature of these devices makes it difficult to discover security and privacy vulnerabilities. This course introduces basic and advanced topics on Internet-of-Things (IoT) security and privacy from a data-driven perspective. It starts with preliminaries on networking and Internet security, followed by security research based on a data-driven approach. Students will read peer-reviewed academic papers from multiple disciplines, ranging from computer science, psychology, and policy/law. Furthermore, students will engage in hands-on projects to independently investigate real-world security and privacy issues of IoT devices and/or propose solutions to fix these issues. Students for this class are expected to have networking knowledge, such as how TCP/IP works, how packets get forwarded, and how to run tcpdump. Otherwise, students are encouraged to take relevant Coursera courses on these topics before the semester begins and to seek the instructor's approval.