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A risk-security tradeoff in graphical coordination games
Systems and Control · Submitted 4 Jun 2019
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim We show that this tradeoff significantly improves when the operator selects a decision-making process at random.
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The abstract, sentence by sentence
A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. How well can a system operator protect performance in the face of these risks? We frame this question in the context of graphical coordination games, where the agents in a network choose among two conventions and derive benefits from coordinating neighbors, and system performance is measured in terms of the agents' welfare. In this paper, we assess an operator's ability to mitigate two types of adversarial attacks - 1) broad attacks, where the adversary incentivizes all agents in the network and 2) focused attacks, where the adversary can force a selected subset of the agents to commit to a prescribed convention. As a mitigation strategy, the system operator can implement a class of distributed algorithms that govern the agents' decision-making process. Our main contribution characterizes the operator's fundamental trade-off between security against worst-case broad attacks and vulnerability from focused attacks. We show that this tradeoff significantly improves when the operator selects a decision-making process at random. Our work highlights the design challenges a system operator faces in maintaining resilience of networked distributed systems.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. | background 1.00 | 0.04 | 0.02 | asserted 0.78 |
| s1 | How well can a system operator protect performance in the face of these risks? | background 0.69 | 0.03 | 0.01 | unclear 0.99 |
| s2 | We frame this question in the context of graphical coordination games, where the agents in a network choose among two conventions and derive benefits from coordinating neighbors, and system performance is measured in terms of the agents' welfare. | background 0.95 | 0.12 | 0.03 | asserted 0.92 |
| s3 | In this paper, we assess an operator's ability to mitigate two types of adversarial attacks - 1) broad attacks, where the adversary incentivizes all agents in the network and 2) focused attacks, where the adversary can force a selected subset of the agents to commit to a prescribed convention. | contribution 0.81 | 0.67 | 0.04 | asserted 0.90 |
| s4 | As a mitigation strategy, the system operator can implement a class of distributed algorithms that govern the agents' decision-making process. | method 0.83 | 0.10 | 0.02 | asserted 0.57 |
| s5 | Our main contribution characterizes the operator's fundamental trade-off between security against worst-case broad attacks and vulnerability from focused attacks. | contribution 0.99 | 0.89 | 0.88 | asserted 0.98 |
| s6 | We show that this tradeoff significantly improves when the operator selects a decision-making process at random. | result 0.99 | 0.93 | 0.41 | asserted 1.00 |
| s7 | Our work highlights the design challenges a system operator faces in maintaining resilience of networked distributed systems. | interpretation 1.00 | 0.26 | 0.06 | asserted 0.94 |
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Original abstract
A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. How well can a system operator protect performance in the face of these risks? We frame this question in the context of graphical coordination games, where the agents in a network choose among two conventions and derive benefits from coordinating neighbors, and system performance is measured in terms of the agents' welfare. In this paper, we assess an operator's ability to mitigate two types of adversarial attacks - 1) broad attacks, where the adversary incentivizes all agents in the network and 2) focused attacks, where the adversary can force a selected subset of the agents to commit to a prescribed convention. As a mitigation strategy, the system operator can implement a class of distributed algorithms that govern the agents' decision-making process. Our main contribution characterizes the operator's fundamental trade-off between security against worst-case broad attacks and vulnerability from focused attacks. We show that this tradeoff significantly improves when the operator selects a decision-making process at random. Our work highlights the design challenges a system operator faces in maintaining resilience of networked distributed systems.
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