Mean-Field-Game Model for Botnet Defense in Cyber-Security

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Mean-Field-Game Model for Botnet Defense in Cyber-Security. / Kolokoltsov, V. N.; Bensoussan, A.

In: Applied Mathematics and Optimization, Vol. 74, No. 3, 01.12.2016, p. 669-692.

Research output: Contribution to journal › Article › peer-review

Author

Kolokoltsov, V. N. ; Bensoussan, A. / Mean-Field-Game Model for Botnet Defense in Cyber-Security. In: Applied Mathematics and Optimization. 2016 ; Vol. 74, No. 3. pp. 669-692.

BibTeX

@article{51ae010003624c25bcc88d5229a41850,

title = "Mean-Field-Game Model for Botnet Defense in Cyber-Security",

abstract = "We initiate the analysis of the response of computer owners to various offers of defence systems against a cyber-hacker (for instance, a botnet attack), as a stochastic game of a large number of interacting agents. We introduce a simple mean-field game that models their behavior. It takes into account both the random process of the propagation of the infection (controlled by the botner herder) and the decision making process of customers. Its stationary version turns out to be exactly solvable (but not at all trivial) under an additional natural assumption that the execution time of the decisions of the customers (say, switch on or out the defence system) is much faster that the infection rates.",

keywords = "Botnet defence, Mean-field game, Phase transitions, Stable equilibrium",

author = "Kolokoltsov, {V. N.} and A. Bensoussan",

year = "2016",

month = dec,

day = "1",

doi = "10.1007/s00245-016-9389-6",

language = "English",

volume = "74",

pages = "669--692",

journal = "Applied Mathematics and Optimization",

issn = "0095-4616",

publisher = "Springer Nature",

number = "3",

}

RIS

TY - JOUR

T1 - Mean-Field-Game Model for Botnet Defense in Cyber-Security

AU - Kolokoltsov, V. N.

AU - Bensoussan, A.

PY - 2016/12/1

Y1 - 2016/12/1

N2 - We initiate the analysis of the response of computer owners to various offers of defence systems against a cyber-hacker (for instance, a botnet attack), as a stochastic game of a large number of interacting agents. We introduce a simple mean-field game that models their behavior. It takes into account both the random process of the propagation of the infection (controlled by the botner herder) and the decision making process of customers. Its stationary version turns out to be exactly solvable (but not at all trivial) under an additional natural assumption that the execution time of the decisions of the customers (say, switch on or out the defence system) is much faster that the infection rates.

AB - We initiate the analysis of the response of computer owners to various offers of defence systems against a cyber-hacker (for instance, a botnet attack), as a stochastic game of a large number of interacting agents. We introduce a simple mean-field game that models their behavior. It takes into account both the random process of the propagation of the infection (controlled by the botner herder) and the decision making process of customers. Its stationary version turns out to be exactly solvable (but not at all trivial) under an additional natural assumption that the execution time of the decisions of the customers (say, switch on or out the defence system) is much faster that the infection rates.

KW - Botnet defence

KW - Mean-field game

KW - Phase transitions

KW - Stable equilibrium

UR - http://www.scopus.com/inward/record.url?scp=84994460480&partnerID=8YFLogxK

U2 - 10.1007/s00245-016-9389-6

DO - 10.1007/s00245-016-9389-6

M3 - Article

AN - SCOPUS:84994460480

VL - 74

SP - 669

EP - 692

JO - Applied Mathematics and Optimization

JF - Applied Mathematics and Optimization

SN - 0095-4616

IS - 3

ER -

ID: 51531096