Cyber-Physical Emulation and Optimization of Worst-Case Cyber Attacks on the Power Grid

Castillo, Anya; Arguello, Bryan; Cruz, Gerardo; Swiler, Laura Painton

doi:10.1109/rws47064.2019.8971996

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…The grid operator then responds through generator redispatch and load shed to minimize unmet demand. This attacker-defender model is adapted for a cyber attacker in [23], though still without modeling the cyber network explicitly.…”

Section: A Literature Reviewmentioning

confidence: 99%

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A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Arguello¹,

Johnson²,

Gearhart³

2021

Preprint

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Network segmentation of a power grid's communication system is one way to make the grid more resilient to cyber attacks. We develop a novel trilevel programming model to optimally segment a grid communication system, taking into account the actions of an information technolology (IT) administrator, attacker, and grid operator. The IT administrator is given an allowance to segment existing networks, and the attacker is given a fixed budget to attack the segmented communication system in an attempt to inflict damage on the grid. Finally, the grid operator is allowed to redispatch the grid after the attack in order to minimize damage. The resulting problem is a trilevel interdiction problem, which we solve by leveraging current research in bilevel branch and bound. We demonstrate the benefits of optimal network segmentation through case studies on the 9-bus WSCC system and the 30-bus IEEE system. These examples illustrate that network segmentation can significantly reduce the threat posed by a cyber attacker with perfect knowledge of the grid. Continuous Variables Grid operator decisions: θ sVoltage angle at substation s p gReal power output of generator g f k Real power flow on line k l dReal power load shed at load d L Real power total load shed

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Section: A Literature Reviewmentioning

confidence: 99%

“…Constraint (22) enforces the attacker's budget. Constraint (23) requires that the attacker can only access enclaves which are controlled by already-accessed enclaves. That is, with respect to the graphs in Fig.…”

Section: Trilevel Formulationmentioning

confidence: 99%

A Trilevel Model for Segmentation of the Power Transmission Grid Cyber Network

Arguello¹,

Johnson²,

Gearhart³

2021

Preprint

Self Cite

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“…Additionally, this bilevel problem could be a subproblem in long-term planning problems such as physical and cyber network design problems seeking to minimize the risk of cyber attacks. The model we solve was originally presented in Castillo et al (2019). We will refer to it as the worst-case relay attack problem.…”

Section: Introductionmentioning

confidence: 99%

A Scalable Lower Bound for the Worst-Case Relay Attack Problem on the Transmission Grid

Johnson¹,

Dey²

2021

Preprint

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We consider a bilevel attacker-defender problem to find the worst-case attack on the relays that control transmission grid components. The attacker infiltrates some number of relays and renders all of the components connected to them inoperable, with the goal of maximizing load shed. The defender responds by minimizing the resulting load shed, re-dispatching using a DC optimal power flow (DCOPF) problem on the remaining network. Though worst-case interdiction problems on the transmission grid have been studied for years, none of the methods in the literature are exact because they rely on assumptions on the bounds of the dual variables of the defender problem in order to reformulate the bilevel problem as a mixed integer linear problem (MILP). The result is a lower bound, and additionally, the more conservatively the dual variables are bounded, the weaker the linear programming relaxations are and hence the more difficult it is to solve the problem at scale. In this work we also present a lower bound, where instead of bounding the dual variables, we drop the constraints corresponding to Ohm's law, relaxing DCOPF to capacitated network flow. This is a restriction of the original bilevel problem. We present theoretical results showing that, for uncongested networks, approximating DCOPF with network flow yields the same set of injections, and thus the same load shed, which suggests that this restriction likely gives a high-quality lower bound in the uncongested case. Furthermore, we show that in this formulation, the duals are bounded by 1, so we can solve our restriction exactly. Last, because the big-M values in the linearization are small and network flow has a well-known structure, we see empirically that this formulation scales well computationally with increased network size. Through our empirical experiments, we find that this bound is almost always as tight as we can get from guessing the dual bounds, even for more congested networks. We demonstrate our results in a case study on ten networks with up to 6468 buses.

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