A Network Monitoring Game with Heterogeneous Component Criticality Levels
Name
1903.07261.pdf
Description
Submitted version
Size
513.48 KB
Format
Adobe PDF
Checksum (MD5)
9d21f15bd0b037bd449bac6ea2e1b7bb
Author(s)
Milosevic, Jezdimir
Dahan, Mathieu
Amin, Saurabh
Sandberg, Henrik
Date Issued
2019
Journal
Proceedings of the IEEE Conference on Decision and Control
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
J. Milošević, M. Dahan, S. Amin and H. Sandberg, "A Network Monitoring Game with Heterogeneous Component Criticality Levels," 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, pp. 4379-4384
Version
Original manuscript
Abstract
We consider an attacker-operator game for monitoring a large-scale network that is comprised of components that differ in their criticality levels. In this zero-sum game, the operator seeks to position a limited number of sensors to monitor the network against the attacker who strategically targets a network component. The operator (resp. attacker) seeks to minimize (resp. maximize) the network loss. To study the properties of mixed-strategy Nash Equilibria of this game, we first study two simple instances: When component sets monitored from individual sensor locations are mutually disjoint; When only a single sensor is positioned, but with possibly overlapping monitoring component sets. Our analysis reveals new insights on how criticality levels impact the players equilibrium strategies. Next, we extend a previously developed approach to obtain an approximate Nash equilibrium in the general case. This approach uses solutions to minimum set cover and maximum set packing problems to construct an approximate Nash equilibrium. Finally, we implement a column generation procedure to improve this solution and numerically evaluate the performance of our approach.
MIT Department
Massachusetts Institute of Technology. Center for Computational Engineering
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CDC40024.2019.9029427
