Driver-Node based Security Analysis for Network Controllability. / Zhang, Shuo; Wolthusen, Stephen.

2019. 1-6 Paper presented at 17th European Control Conference (ECC19), Naples, Italy.

Research output: Contribution to conferencePaper

Published

Standard

Driver-Node based Security Analysis for Network Controllability. / Zhang, Shuo; Wolthusen, Stephen.

2019. 1-6 Paper presented at 17th European Control Conference (ECC19), Naples, Italy.

Research output: Contribution to conferencePaper

Harvard

Zhang, S & Wolthusen, S 2019, 'Driver-Node based Security Analysis for Network Controllability' Paper presented at 17th European Control Conference (ECC19), Naples, Italy, 25/06/19 - 29/06/19, pp. 1-6. https://doi.org/10.23919/ECC.2019.8796264

APA

Zhang, S., & Wolthusen, S. (2019). Driver-Node based Security Analysis for Network Controllability. 1-6. Paper presented at 17th European Control Conference (ECC19), Naples, Italy. https://doi.org/10.23919/ECC.2019.8796264

Vancouver

Zhang S, Wolthusen S. Driver-Node based Security Analysis for Network Controllability. 2019. Paper presented at 17th European Control Conference (ECC19), Naples, Italy. https://doi.org/10.23919/ECC.2019.8796264

Author

Zhang, Shuo ; Wolthusen, Stephen. / Driver-Node based Security Analysis for Network Controllability. Paper presented at 17th European Control Conference (ECC19), Naples, Italy.6 p.

BibTeX

@conference{1a3ada7dcb044dc2b63f62632e413ae8,
title = "Driver-Node based Security Analysis for Network Controllability",
abstract = "In the study of network controllability, because driver nodes are vulnerable to control hijack and removals, and harmfulness of removing a driver node is still unknown. Therefore, to defend against such attacks, we identify each vertex of all minimum sets of driver nodes firstly. Also, to know the harmfulness of removing a driver node, we classify those identified nodes by impacts of removing a driver node on the minimum set of driver nodes to control the residual network. By the minimum input theorem, given a digraph, these two issues are respectively solved by finding each vertex that is an unmatched node related to a maximum matching, and classifying it by the impact of its removal on the number of unmatched nodes of the residual digraph. As a result, our driver-node identification and classification are executed in more efficient polynomial time than related works.",
author = "Shuo Zhang and Stephen Wolthusen",
year = "2019",
month = "8",
day = "15",
doi = "10.23919/ECC.2019.8796264",
language = "English",
pages = "1--6",
note = "17th European Control Conference (ECC19), ECC 2019 ; Conference date: 25-06-2019 Through 29-06-2019",

}

RIS

TY - CONF

T1 - Driver-Node based Security Analysis for Network Controllability

AU - Zhang, Shuo

AU - Wolthusen, Stephen

PY - 2019/8/15

Y1 - 2019/8/15

N2 - In the study of network controllability, because driver nodes are vulnerable to control hijack and removals, and harmfulness of removing a driver node is still unknown. Therefore, to defend against such attacks, we identify each vertex of all minimum sets of driver nodes firstly. Also, to know the harmfulness of removing a driver node, we classify those identified nodes by impacts of removing a driver node on the minimum set of driver nodes to control the residual network. By the minimum input theorem, given a digraph, these two issues are respectively solved by finding each vertex that is an unmatched node related to a maximum matching, and classifying it by the impact of its removal on the number of unmatched nodes of the residual digraph. As a result, our driver-node identification and classification are executed in more efficient polynomial time than related works.

AB - In the study of network controllability, because driver nodes are vulnerable to control hijack and removals, and harmfulness of removing a driver node is still unknown. Therefore, to defend against such attacks, we identify each vertex of all minimum sets of driver nodes firstly. Also, to know the harmfulness of removing a driver node, we classify those identified nodes by impacts of removing a driver node on the minimum set of driver nodes to control the residual network. By the minimum input theorem, given a digraph, these two issues are respectively solved by finding each vertex that is an unmatched node related to a maximum matching, and classifying it by the impact of its removal on the number of unmatched nodes of the residual digraph. As a result, our driver-node identification and classification are executed in more efficient polynomial time than related works.

U2 - 10.23919/ECC.2019.8796264

DO - 10.23919/ECC.2019.8796264

M3 - Paper

SP - 1

EP - 6

ER -