Title | MILP Modeling of Targeted False Load Data Injection Cyberattacks to Overflow Transmission Lines in Smart Grids |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Khezrimotlagh, Darius, Khazaei, Javad, Asrari, Arash |
Conference Name | 2019 North American Power Symposium (NAPS) |
Date Published | oct |
Keywords | attack model, bad data detection constraints, bi-level mixed integer linear programming optimization model, composability, cyber physical systems, cyberattack, Data models, False Data Detection, False Data Injection, Human Behavior, IEEE 118-bus power system, Load flow, Load modeling, MILP modeling, Mixed Integer Linear Programming (MILP), optimal power flow constraints, optimal power flow problem, optimisation, optimized false data injections, overflow transmission lines, power system security, power system simulation, power system state estimation, power transmission lines, pubcrawl, resilience, Resiliency, security, security of data, Smart grids, smart power grids, targeted false load data injection cyberattacks, targeted load buses, targeted transmission line, Transmission Line Congestion, Transmission line measurements, upper level optimization problem |
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. |
DOI | 10.1109/NAPS46351.2019.8999977 |
Citation Key | khezrimotlagh_milp_2019 |