A novel method to detect bad data injection attack in smart grid

Ting Liu; Yun Gu; Dai Wang; Yuhong Gui; Xiaohong Guan

doi:10.1109/INFCOMW.2013.6562907

A novel method to detect bad data injection attack in smart grid

Ting Liu
, Yun Gu
, Dai Wang
, Yuhong Gui
, Xiaohong Guan

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Scopus citations

Abstract

Bad data injection is one of most dangerous attacks in smart grid, as it might lead to energy theft on the end users and device breakdown on the power generation. The attackers can construct the bad data evading the bad data detection mechanisms in power system. In this paper, a novel method, named as Adaptive Partitioning State Estimation (APSE), is proposed to detect bad data injection attack. The basic ideas are: 1) the large system is divided into several subsystems to improve the sensitivity of bad data detection; 2) the detection results are applied to guide the subsystem updating and re-partitioning to locate the bad data. Two attack cases are constructed to inject bad data into an IEEE 39-bus system, evading the traditional bad data detection mechanism. The experiments demonstrate that all bad data can be detected and located within a small area using APSE.

Original language	English
Title of host publication	2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013
Publisher	IEEE Computer Society
Pages	49-54
Number of pages	6
ISBN (Print)	9781479900565
DOIs	https://doi.org/10.1109/INFCOMW.2013.6562907
State	Published - 2013
Event	2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013 - Turin, Italy Duration: 14 Apr 2013 → 19 Apr 2013

Publication series

Name	2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013

Conference

Conference	2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013
Country/Territory	Italy
City	Turin
Period	14/04/13 → 19/04/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

adaptive partitioning state estimation
bad data injection
detection
security
smart grid

Access to Document

10.1109/INFCOMW.2013.6562907

Cite this

Liu, T., Gu, Y., Wang, D., Gui, Y., & Guan, X. (2013). A novel method to detect bad data injection attack in smart grid. In 2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013 (pp. 49-54). Article 6562907 (2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013). IEEE Computer Society. https://doi.org/10.1109/INFCOMW.2013.6562907

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title = "A novel method to detect bad data injection attack in smart grid",

abstract = "Bad data injection is one of most dangerous attacks in smart grid, as it might lead to energy theft on the end users and device breakdown on the power generation. The attackers can construct the bad data evading the bad data detection mechanisms in power system. In this paper, a novel method, named as Adaptive Partitioning State Estimation (APSE), is proposed to detect bad data injection attack. The basic ideas are: 1) the large system is divided into several subsystems to improve the sensitivity of bad data detection; 2) the detection results are applied to guide the subsystem updating and re-partitioning to locate the bad data. Two attack cases are constructed to inject bad data into an IEEE 39-bus system, evading the traditional bad data detection mechanism. The experiments demonstrate that all bad data can be detected and located within a small area using APSE.",

keywords = "adaptive partitioning state estimation, bad data injection, detection, security, smart grid",

author = "Ting Liu and Yun Gu and Dai Wang and Yuhong Gui and Xiaohong Guan",

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series = "2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013",

publisher = "IEEE Computer Society",

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note = "2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013 ; Conference date: 14-04-2013 Through 19-04-2013",

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Liu, T, Gu, Y, Wang, D, Gui, Y & Guan, X 2013, A novel method to detect bad data injection attack in smart grid. in 2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013., 6562907, 2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013, IEEE Computer Society, pp. 49-54, 2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013, Turin, Italy, 14/04/13. https://doi.org/10.1109/INFCOMW.2013.6562907

A novel method to detect bad data injection attack in smart grid. / Liu, Ting; Gu, Yun; Wang, Dai et al.
2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013. IEEE Computer Society, 2013. p. 49-54 6562907 (2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel method to detect bad data injection attack in smart grid

AU - Liu, Ting

AU - Gu, Yun

AU - Wang, Dai

AU - Gui, Yuhong

AU - Guan, Xiaohong

PY - 2013

Y1 - 2013

N2 - Bad data injection is one of most dangerous attacks in smart grid, as it might lead to energy theft on the end users and device breakdown on the power generation. The attackers can construct the bad data evading the bad data detection mechanisms in power system. In this paper, a novel method, named as Adaptive Partitioning State Estimation (APSE), is proposed to detect bad data injection attack. The basic ideas are: 1) the large system is divided into several subsystems to improve the sensitivity of bad data detection; 2) the detection results are applied to guide the subsystem updating and re-partitioning to locate the bad data. Two attack cases are constructed to inject bad data into an IEEE 39-bus system, evading the traditional bad data detection mechanism. The experiments demonstrate that all bad data can be detected and located within a small area using APSE.

AB - Bad data injection is one of most dangerous attacks in smart grid, as it might lead to energy theft on the end users and device breakdown on the power generation. The attackers can construct the bad data evading the bad data detection mechanisms in power system. In this paper, a novel method, named as Adaptive Partitioning State Estimation (APSE), is proposed to detect bad data injection attack. The basic ideas are: 1) the large system is divided into several subsystems to improve the sensitivity of bad data detection; 2) the detection results are applied to guide the subsystem updating and re-partitioning to locate the bad data. Two attack cases are constructed to inject bad data into an IEEE 39-bus system, evading the traditional bad data detection mechanism. The experiments demonstrate that all bad data can be detected and located within a small area using APSE.

KW - adaptive partitioning state estimation

KW - bad data injection

KW - detection

KW - security

KW - smart grid

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M3 - 会议稿件

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BT - 2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013

PB - IEEE Computer Society

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Y2 - 14 April 2013 through 19 April 2013

ER -

A novel method to detect bad data injection attack in smart grid

Abstract

Publication series

Conference

UN SDGs

Keywords

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