Doctoral Dissertations


Cyber-Physical Systems (CPS) are sensing, processing, and communicating platforms, embedded with physical devices that provide real-time monitoring and control. Security challenges in CPS necessitate solutions that are robust against attacks and uncertainties and provide a seamless operation, especially when used in real-time applications to monitor and secure critical infrastructures. CPS mainly consists of a physical component for sensing or monitoring and a cyber component for processing and communicating. The quality of interactions between physical and cyber systems has direct impacts on the system’s performance and reliability.

CPS plays a major role in smart services and applications within a smart living environment, such as smart cities, smart energy management systems, traffic control, critical infrastructure protection, and many defense-related systems. Such smart CPS are integrating sensing, communication, computation, and control aim to achieve stability, high performance, robustness, and efficiency. This thesis concentrates on three aspects of CPS robustness and security. First, we investigate the security of smart grid systems against adversarial attacks and how reliable automation of smart grids depends on decisions based on situational awareness extracted via real-time system monitoring. Second, we take a crowdsourcing vehicular network environment to identify potential security concerns, specifically that impacts the quantification of aggregate truthfulness of events (quality of information or QoI). Finally, we generalize the CPS system to create a large-scale network to investigate how information propagates in the CPS network and possible ways to control and mitigate the information spread. In all these cases, we identify the attack strategies that can be employed by an intelligent adversarial entity to disrupt the operation of the application and how different measures can be developed to make the system more robust and resilient against attacks and uncertainties”--Abstract, page iii.


Das, Sajal K.

Committee Member(s)

Bhattacharjee, Shameek
Nadendla, V. Sriram Siddhardh
Luo, Tony Tie
Cen, Nan


Computer Science

Degree Name

Ph. D. in Computer Science


The author would like to acknowledge the National Science Foundation for supporting this work with NSF grants CNS-1545050, CNS-1818942, and SaTC-2030624.


Missouri University of Science and Technology

Publication Date

Fall 2021


xiii, 121 pages

Note about bibliography

Includes bibliographic references (pages 112-120).


© 2021 Prithwiraj Roy, All rights reserved.

Document Type

Dissertation - Open Access

File Type




Thesis Number

T 11963