An evolutionary game for integrity attacks and defences for advanced metering infrastructure

Boudko, Svetlana; Abie, Habtamu

doi:10.1145/3241403.3241463

Cited by 11 publications

(8 citation statements)

References 31 publications

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“…We can combine Equations ( 11)-( 14) with the evolutionary replicator dynamic with noise [43] to model the evolution of any set of strategies. For any subset of attacking strategies S ⊂ S, the evolutionary replicator dynamic with noise [43] takes the form of dP s dτ ( S) = S(π A (s , P t ) − π A (P s , P t ))P s (ds ) + δ S ( S), (15) for some time scale τ and a stochastic term δ s ( S). Similarly, the evolution of a subset of defending strategies T ⊂ T is given by…”

Section: Evolutionary Game Formulationmentioning

confidence: 99%

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Evolutionary Game for Confidentiality in IoT-Enabled Smart Grids

2020

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We applied evolutionary game theory to extend a resource constrained security game model for confidentiality attacks and defenses in an Advanced Metering Infrastructure (AMI), which is a component of IoT-enabled Smart Grids. The AMI is modeled as a tree structure where each node aggregates the information of its children before encrypting it and passing it on to its parent. As a part of the model, we developed a discretization scheme for solving the replicator equations. The aim of this work was to explore the space of possible behaviors of attackers and to develop a framework where the AMI nodes adaptively select the most profitable strategies. Using this model, we simulated the evolution of a population of attackers and defenders on various cases resembling the real life implementation of AMI. We discuss in depth how to enhance security in AMI using evolutionary game theory either by a priori analysis or as a tool to run dynamic and adaptive infrastructure defense.

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Section: Evolutionary Game Formulationmentioning

confidence: 99%

“…Previously, we have introduced an evolutionary game framework [15] that models evolving attacks and defenses in connection with data integrity for smart grid systems. The novel contributions of this paper are:…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Game for Confidentiality in IoT-Enabled Smart Grids

2020

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“…e evolutionary process of the attack and defense strategies in the continuous confrontation process was also analyzed. Reference [18] took aim at the security problems faced by intelligent networks and proposed a network attack and defense framework based on an evolutionary game model using a replicative dynamic learning mechanism and also investigated how to maximize defense return with limited node resources.…”

Section: Introductionmentioning

confidence: 99%

Optimal Network Defense Strategy Selection Method Based on Evolutionary Network Game

Liu¹,

Zhang²,

Zhang³

et al. 2020

Security and Communication Networks

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The basic hypothesis of evolutionary game theory is that the players in the game possess limited rationality. The interactive behavior of players can be described by a learning mechanism that has theoretical advantages in modeling the network security problem in a real society. The current network security evolutionary game model generally adopts a replicator dynamic learning mechanism and assumes that the interaction between players in the group conforms to the characteristics of uniform mixed distribution. However, in an actual network attack and defense scenario, the players in the game have limited learning capability and can only interact with others within a limited range. To address this, we improved the learning mechanism based on the network topology, established the learning object set based on the learning range of the players, used the Fermi function to calculate the transition probability to the learning object strategy, and employed random noise to describe the degree of irrational influence in the learning process. On this basis, we built an attack and defense evolutionary network game model, analyzed the evolutionary process of attack and defense strategy, solved the evolution equilibrium, and designed a defense strategy selection algorithm. The effectiveness of the model and method is verified by conducting simulation experiments for the transition probability of the players and the evolutionary process of the defense group strategy.

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“…Previously, we have introduced an evolutionary game framework [14] that models evolving attacks and defenses in connection with data integrity for smart grid systems. The novel contributions of this paper are:…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Game for Confidentiality in IoT-enabled Smart Grids

Boudko¹,

Aursand²,

Abie³

2020

Preprint

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We applied evolutionary game theory to extend a resource constrained security game model for confidentiality attacks in an Advanced Metering Infrastructure (AMI), which is a component of IoT-enabled Smart Grids. The AMI is modelled as a tree structure where each node aggregates the information of its children before encrypting it and passing it on to its parent. As a part of the model, we developed a discretization scheme for solving the replicator equations. The aim of this work is to explore the space of possible behaviours of attackers and to develop a framework where the AMI nodes adaptively select the most profitable strategies. Using this model, we simulated the evolution of a population of attackers and defenders on various cases resembling the real life implementation of AMI. We discuss in depth how to enhance security in AMI using evolutionary game theory either by a priori analysis or as a tool to run dynamic and adaptive infrastructure defence.

show abstract

An evolutionary game for integrity attacks and defences for advanced metering infrastructure

Cited by 11 publications

References 31 publications

Evolutionary Game for Confidentiality in IoT-Enabled Smart Grids

Evolutionary Game for Confidentiality in IoT-Enabled Smart Grids

Optimal Network Defense Strategy Selection Method Based on Evolutionary Network Game

Evolutionary Game for Confidentiality in IoT-enabled Smart Grids

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