MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids

Darius Khezrimotlagh; Javad Khazaei; Arash Asrari

doi:10.1109/NAPS46351.2019.8999977

MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids

Darius Khezrimotlagh, Javad Khazaei, Arash Asrari

School of Science, Engineering & Technology (Harrisburg)

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

22 Scopus citations

Abstract

Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.

Original language	English (US)
Title of host publication	51st North American Power Symposium, NAPS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728104072
DOIs	https://doi.org/10.1109/NAPS46351.2019.8999977
State	Published - Oct 2019
Event	51st North American Power Symposium, NAPS 2019 - Wichita, United States Duration: Oct 13 2019 → Oct 15 2019

Publication series

Name	51st North American Power Symposium, NAPS 2019

Conference

Conference	51st North American Power Symposium, NAPS 2019
Country/Territory	United States
City	Wichita
Period	10/13/19 → 10/15/19

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Hardware and Architecture
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality

UN SDGs

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

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10.1109/NAPS46351.2019.8999977

Cite this

Khezrimotlagh, D., Khazaei, J., & Asrari, A. (2019). MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids. In 51st North American Power Symposium, NAPS 2019 Article 8999977 (51st North American Power Symposium, NAPS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAPS46351.2019.8999977

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title = "MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids",

abstract = "Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.",

author = "Darius Khezrimotlagh and Javad Khazaei and Arash Asrari",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 51st North American Power Symposium, NAPS 2019 ; Conference date: 13-10-2019 Through 15-10-2019",

year = "2019",

month = oct,

doi = "10.1109/NAPS46351.2019.8999977",

language = "English (US)",

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Khezrimotlagh, D, Khazaei, J & Asrari, A 2019, MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids. in 51st North American Power Symposium, NAPS 2019., 8999977, 51st North American Power Symposium, NAPS 2019, Institute of Electrical and Electronics Engineers Inc., 51st North American Power Symposium, NAPS 2019, Wichita, United States, 10/13/19. https://doi.org/10.1109/NAPS46351.2019.8999977

MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids. / Khezrimotlagh, Darius; Khazaei, Javad; Asrari, Arash.
51st North American Power Symposium, NAPS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8999977 (51st North American Power Symposium, NAPS 2019).

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

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T1 - MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids

AU - Khezrimotlagh, Darius

AU - Khazaei, Javad

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PY - 2019/10

Y1 - 2019/10

N2 - Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.

AB - Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.

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M3 - Conference contribution

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T3 - 51st North American Power Symposium, NAPS 2019

BT - 51st North American Power Symposium, NAPS 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 51st North American Power Symposium, NAPS 2019

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MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids

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UN SDGs

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