Announcements

If you already meet the prerequisites, please directly register for the course on Banner (EECE 5698 ST Section 8).


If you do not yet meet the prerequisites but would like to ask for the instructor's approval, or ask any other questions, please use this Google Form to submit inquiry.

Class meets Mon/Thu 11:45AM-1:25PM in Hayden 009A

This lab-based special topics course explores the signal physics and Fourier domain analysis of emerging cyber-physical systems' security and privacy. Through experiential learning, students will model, measure, and secure embedded systems and IoT devices, focusing on the hardware-software interfaces. The course will have a particular focus on the interface between hardware and software and the physics of computation, as well as their impact on downstream control systems that could employ AI technologies. Included in the IoT security topic is a deep dive on security of Operational Technology (OT) such as found in high-assurance factory floors, and Microelectrical Mechanical Systems (MEMS) technology common in IoT, automotive, medical, RFID, and satellites. Hands-on lab exercises will involve frequency-domain analysis of signals, voice recognition system integrity and authenticity, acoustics both audible and ultrasonic, radio waves and modulation, and laser fault injection of semiconductors. The semester will culminate with a group project and demonstrations. Short essays will give individual students the opportunity to explore the application of the new skills and methods to design secure implantable medical devices, automobiles, and smartphones. Students will be required to complete safety training and will gain comfort with working in a maker space. By the end of the course, students will become comfortable safely creating signals with acoustics, radios, and lasers to test the security of embedded systems and measure their impact on prevalent AI-based control algorithms.

Course Prerequisites: At least one of the following courses, or permission of instructor:

• EECE 2160 (Embedded Design: Enabling Robotics)
• EECE 2412 (Fundamentals of Electronics)
• EECE 4534 (Microprocessor-Based Design)
• EECS 5515 (Wireless Sensor Networks and the Internet of Things)
• EECE 5666 (Digital Signal Processing)

Course Topics:

• Part 1: Building Blocks: Threat modeling based on physics, principles of information security and privacy, risk, research ethics
• Part 2: Embedded Security: Side channels, spectral analysis, timing attacks, power analysis, data remanence
• Part 3: Sensor Security: Physics of security, transducers, MEMS, audible and ultrasonic acoustics, RF, optics
• Part 4: Internet of Things (IoT) & Operational Technology (OT): Factory floors, robotics, advanced manufacturing, medical devices, smart homes
• Part 5: Machine Learning (ML) and Artificial Intelligence (AI): Embedded security for ML and AI

FAQ:

• 0. Q: How do I contact the instructors?
  A: Please ensure you first read the course website and FAQ thoroughly. If the FAQ does not answer your question, use the form to submit a query to the course staff. Because of the popularity of the course, any emailed questions will be redirected to this form. So please only use this form to contact the instructors and refrain from sending any emails directly.
• 1. Q: I am not an ECE major. Can I sign up for this course?
  A: There is no requirement to be an ECE major. If you have taken the prerequisites, you may directly sign up on Banner. If not, we ask you to complete the quiz questions in this form to ask for the instructor's consideration for approval to enroll.
• 2. Q: Can I succeed in this course if I didn't have any ECE or cybersecurity background?
  A: Yes, you could succeed. The key requirement is basic understandings of signals and systems. You are welcome to teach yourself and answer the quiz questions that help gauge your preparedness to take this course. The course has many hands-on labs combining physics and signals and systems as well as basic computer security tasks.
• 3. Q: What are the components of this course?
  A: The course grade is primarily composed of the following five components:
  - Class Participation and Presentation - 5%
  - Essays - 15%
  - Hands-on Labs - 30%
  - Midterm - 15%
  - Final Group Project - 35%