Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

Title: “Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis”
Name: Sujit Rokka Chhetri

Date: May 20, 2019

Time: 3:00 PM

Location: EH 5200

Committee: Prof. Mohammad Al Faruque (Chair), Prof. Pramod Khargonekar, Prof. Fadi Kurdahi

Abstract:

Cyber-Physical System consists of the integration of computational components in the cyber-domain with the physical-domain processes. In cyber-domain, embedded computers and networks monitor and control the physical processes, and in the physical-domain the sensors and actuators aid in interacting with the physical world. This interaction between the cyber and physical domain brings unique modeling challenges one of which includes the integration of discrete models in cyber-domain with the continuous physical domain processes. However, the same cyber-physical interaction also opens new opportunities for modeling. For example, the information flow in the cyber-domain manifests physically in the form of energy flows in the physical domain. Some of these energy flows unintentionally provide information about the cyber-domain through the side-channels.

In this thesis, the extensive analysis of the side-channels (such as acoustic, magnetic, thermal, power and vibration) of the cyber-physical system is performed. Based on this analysis data-driven models are estimated. These models are then used to perform security vulnerability analysis (for confidentiality and integrity), whereby, new attack models are explored.  Furthermore, the data-driven models are also utilized to create a defensive mechanism to minimize the information leakage from the system and to detect attacks to the integrity of the system. The cyber-physical manufacturing systems are taken as use cases to demonstrate the applicability of the modeling approaches.

Finally, the side-channel analysis is also performed to aid in modeling digital twins of the cyber-physical systems. Specifically, a novel methodology to utilize low-end sensors to analyze the side-channels and build the digital twins is proposed. These digital twins are used to capture the interaction between the cyber-domain and the physical domain of the manufacturing systems, and aid in process quality inference and fault localization. Using side-channels these digital twins are kept up-to-date, which is one of the fundamental requirements for building digital twins.