Welcome to the Interactive Agenda for SecurityWeek’s 2020 ICS Cyber Security Conference! (View the full conference website and register for the conference here)

Back To Schedule
Tuesday, October 20 • 1:15pm - 1:45pm
Identifying Process Structure and Parameters Using Side-channel Information

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.
When securing a cyber-physical system (CPS), the most commonly used methods focus CPS itself, including both the information technology (IT) and operation technology (OT) domains. While such domains are most tightly associated with the underlying systems and thus can block most of the active and passive attack vectors, physical side channel has inevitably become an important source of information leakage, which can be a form of passive attack or even a pre-sequel of an active and orchestrated attack. The use of physical side channels to infer information about a (presumably secure) system has been demonstrated to be effective in many areas, such as reconstructing the object being printed with 3D printers through the sound emitted, or detect the leaking information about the underlying cryptographic computation in a CMOS from its electromagnetic emanations. In this research, audio channel information is leveraged as side channel information of an operating CPS to study the feasibility of identifying the process parameters using the side channel information. More specifically, the types of devices, their operation status and their locations in space are inferred from the audio recorded using microphones. Convolutional neural network (CNN) is employed to learn and predict these parameters based on the transformed audio data. The result demonstrates that with only a small amount of training data, CNN can correctly predict the operation status of individual devices in a realistic water treatment testbed with approximately 100% accuracy.


Qinchen Gu

Software Engineer, Google
Qinchen Gu is currently working as a software engineer at Google. He obtained his PhD degree in ECE at Georgia Institute of Technology in 2020. His research focuses on Cyber-Physical System security, specifically in the area of industrial control systems. His work entails exploiting... Read More →

Raheem Beyah

Georgia Institute of Technology
Raheem Beyah, a native of Atlanta, Ga., is a Professor in the School of Electrical and Computer Engineering at Georgia Tech where he leads the Communications Assurance and Performance Group (CAP) and is a member of the Institute for Information Security & Privacy (IISP) and the Communications... Read More →

Chuadhry Mujeeb Ahmed

Singapore University of Technology and Design (SUTD)

Tuesday October 20, 2020 1:15pm - 1:45pm EDT