"Cyber-physical systems, where computing and communication are used to fortify and streamline the operation of a physical infrastructure, now comprise the foundation of much of modern critical infrastructure. These systems are typically large in scale and highly interconnected, and span application domains from power and water distribution to autonomous vehicle control and collaborative robotics. Intelligent decision support in these systems is heavily reliant on the availability of sufficient and sufficiently correct data. Failure or malfunction of these systems can have devastating consequences in terms of public safety, financial losses, or both.
The research described in this thesis aims to predict the impact of loss or corruption of data on operation of a cyber-physical system. Given knowledge of the respective physical and functional topologies of the system, information exchange is abstracted as a graph of interconnected data processing nodes. A model is created with each node modeled as a stochastic colored Petri net. Populated with information about the reliability of measurement, communication, storage, and processing devices, the Petri net model enables estimation of the fraction of the node's data that will be lost or corrupted.
A determination is made of each node's criticality, based on the consequences of its failure on overall system-level operation, using field data or simulation. The measure of data corruption impact at a given node is the product of the two aforementioned metrics: i) the extent of data corruption expected at the node and ii) its criticality. The proposed approach can enable informed decisions about targeted investments in hardening of cyber-physical system, specifically to mitigate the effects of corruption or loss of data"--Abstract, page iii.
Hurson, A. R.
Çetinkaya, Egemen K.
Electrical and Computer Engineering
M.S. in Computer Engineering
Missouri University of Science and Technology
viii, 48 pages
Note about bibliography
Includes bibliographical references (pages 45-47).
© 2017 Erik David Burgdorf, All rights reserved.
Thesis - Open Access
Electronic OCLC #
Burgdorf, Erik David, "Predicting the impact of data corruption on the operation of cyber-physical systems" (2017). Masters Theses. 7874.