國立虎尾科技大學 |

Low Latency Intrusion Detection in Smart Grids.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Low Latency Intrusion Detection in Smart Grids./
Author:	Akingeneye, Israel.
Description:	1 online resource (132 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Contained By:	Dissertation Abstracts International79-09B(E).
Subject:	Electrical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9780355911565

Low Latency Intrusion Detection in Smart Grids.
Akingeneye, Israel.

Low Latency Intrusion Detection in Smart Grids. - 1 online resource (132 pages)

Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.

Thesis (Ph.D.)--University of Arkansas, 2018.

Includes bibliographical references

The transformation of traditional power grids into smart grids has seen more new technologies such as communication networks and smart meters (sensors) being integrated into the physical infrastructure of the power grids. However, these technologies pose new vulnerabilities to the cybersecurity of power grids as malicious attacks can be launched by adversaries to attack the smart meters and modify the measurement data collected by these meters. If not timely detected and removed, these attacks may lead to inaccurate system state estimation, which is critical to the system operators for control decisions such as economic dispatch and other related functions.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355911565Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Low Latency Intrusion Detection in Smart Grids.
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100 1 $a Akingeneye, Israel. $3 1191089
245 1 0 $a Low Latency Intrusion Detection in Smart Grids.
264 0 $c 2018
300 $a 1 online resource (132 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
500 $a Adviser: Jingxian Wu.
502 $a Thesis (Ph.D.)--University of Arkansas, 2018.
504 $a Includes bibliographical references
520 $a The transformation of traditional power grids into smart grids has seen more new technologies such as communication networks and smart meters (sensors) being integrated into the physical infrastructure of the power grids. However, these technologies pose new vulnerabilities to the cybersecurity of power grids as malicious attacks can be launched by adversaries to attack the smart meters and modify the measurement data collected by these meters. If not timely detected and removed, these attacks may lead to inaccurate system state estimation, which is critical to the system operators for control decisions such as economic dispatch and other related functions.
520 $a This dissertation studies the challenges associated with cyberattacks in power grids and develops solutions to effectively and timely detect these attacks to ensure an accurate state estimation. One of the common approaches to improving the state estimation accuracy is to incorporate phasor measurement unit (PMU) devices into the system to provide extra and more secure measurements. In this research, we design algorithms that place PMUs at strategic locations to enhance the system's state estimation accuracy and its capability to detect cyberattacks. This approach of installing PMU devices in power grids, nonetheless, does not guarantee a timely attack detection that is critical for a timely deployment of countermeasures to prevent catastrophic impacts from the attacks. Thus, the low latency intrusion detection problem is studied to reduce attack detection delays. The state estimation and intrusion detection problem is further extended to a dynamic power system, where there are sudden changes in system loads.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Arkansas. $b Electrical Engineering. $3 1182918
773 0 $t Dissertation Abstracts International $g 79-09B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10812917 $z click for full text (PQDT)