ISE Seminar: Cyberattack Detection for Industrial Cyber-Physical Systems & Critical Infrastructures

Warning Icon This event is in the past.

Date: October 5, 2022
Time: 11:00 a.m. - 12:00 p.m.
Location: Virtual event
Category: Seminar

Abstract

Initiatives like Industry 4.0 and technological frameworks such as the Internet-of-Things have prompted a growing wave of digital transformation across numerous industrial sectors ranging from manufacturing and power generation industries to critical infrastructure systems like waste-water management and natural gas pipeline networks. A big part of this transformation is enabled by the declining costs of sensor technologies, faster and more reliable wireless communications like 5G, and sophisticated plug-and-play industrial control systems (ICSs). Historically, ICSs used to have their own proprietary networks that were difficult to penetrate due to their isolation from the internet. The increased connectivity brought about by digital transformation has created unique cybersecurity vulnerabilities. This talk will focus on detecting cyberattacks that target the physical performance of critical systems and capital-intensive assets. I will discuss a novel framework that combines system modeling and statistical learning for detecting and localizing cyberattacks in a typical complex ICS network – the smart grid, in near real-time. I will also briefly talk about some other ongoing collaborative research on cyber-physical system cybersecurity.


Biography

Dan Li is an assistant professor in the Department of Industrial Engineering at Clemson University. She received her Ph.D. in Industrial Engineering and M.S. in Statistics from Georgia Institute of Technology in 2021 and 2020, respectively. She received her B.S. in Mechanical (Automotive) Engineering from Tsinghua University, Beijing, China, in 2015. Her research interests include cybersecurity for Cyber-Physical Systems (CPS) / Industrial Internet of Things (IIoT), machine learning applications, sensor-based anomaly detection, and complex system modeling. Specifically, she is interested in developing new data-driven algorithms that are tailored for securing CPSs. Dan is the recipient of the Best Track Paper Award in Data Analytics and Information Systems (DAIS) and has been recognized in Best Student Paper Competitions in Energy Systems, DAIS, and Quality Control and Reliability Engineering (QCRE) divisions at the IISE Annual Conferences.


Zoom Information:

Join Zoom Meeting or https://wayne-edu.zoom.us/j/97615785223?pwd=eWtRbXdpMG9GcmIvRjdvLzZkRmhBUT09

Meeting ID: 976 1578 5223

Passcode: 496397

October 2022
SU M TU W TH F SA
2526272829301
2345678
9101112131415
16171819202122
23242526272829
303112345