5,571 research outputs found
Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks
This paper studies the vulnerability of large-scale power systems to false
data injection (FDI) attacks through their physical consequences. Prior work
has shown that an attacker-defender bi-level linear program (ADBLP) can be used
to determine the worst-case consequences of FDI attacks aiming to maximize the
physical power flow on a target line. This ADBLP can be transformed into a
single-level mixed-integer linear program, but it is hard to solve on large
power systems due to numerical difficulties. In this paper, four
computationally efficient algorithms are presented to solve the attack
optimization problem on large power systems. These algorithms are applied on
the IEEE 118-bus system and the Polish system with 2383 buses to conduct
vulnerability assessments, and they provide feasible attacks that cause line
overflows, as well as upper bounds on the maximal power flow resulting from any
attack.Comment: 6 pages, 5 figure
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition
This paper studies the vulnerability of phasor measurement units (PMUs) to
false data injection (FDI) attacks. Prior work demonstrated that unobservable
FDI attacks that can bypass traditional bad data detectors based on measurement
residuals can be identified by detector based on low-rank decomposition (LD).
In this work, a class of more sophisticated FDI attacks that captures the
temporal correlation of PMU data is introduced. Such attacks are designed with
a convex optimization problem and can always bypass the LD detector. The
vulnerability of this attack model is illustrated on both the IEEE 24-bus RTS
and the IEEE 118-bus systems.Comment: 6 pages, 4 figures, submitted to 2017 IEEE International Conference
on Smart Grid Communications (SmartGridComm
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