An Initial Study of Targeted Personality Models in the FlipIt Game

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00329643" target="_blank" >RIV/68407700:21230/18:00329643 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-01554-1_36" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-01554-1_36</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-01554-1_36" target="_blank" >10.1007/978-3-030-01554-1_36</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Initial Study of Targeted Personality Models in the FlipIt Game

Popis výsledku v původním jazyce

Game theory typically assumes rational behavior for solution concepts such as Nash equilibrium. However, this assumption is often violated when human agents are interacting in real-world scenarios, such as cybersecurity. There are different human factors that drive human decision making, and these also vary significantly across individuals leading to substantial individual differences in behavior. Predicting these differences in behavior can help a defender to predict actions of different attacker types to provide better defender strategy tailored towards different attacker types. We conducted an initial study of this idea using a behavioral version of the FlipIt game. We show that there are identifiable differences in behavior among different groups (e.g., individuals with different Dark Triad personality scores), but our initial attempts at capturing these differences using simple known behavioral models does not lead to significantly improved defender strategies. This suggests that richer behavioral models are needed to effectively predict and target strategies in these more complex cybersecurity game.

Název v anglickém jazyce

An Initial Study of Targeted Personality Models in the FlipIt Game

Popis výsledku anglicky

Game theory typically assumes rational behavior for solution concepts such as Nash equilibrium. However, this assumption is often violated when human agents are interacting in real-world scenarios, such as cybersecurity. There are different human factors that drive human decision making, and these also vary significantly across individuals leading to substantial individual differences in behavior. Predicting these differences in behavior can help a defender to predict actions of different attacker types to provide better defender strategy tailored towards different attacker types. We conducted an initial study of this idea using a behavioral version of the FlipIt game. We show that there are identifiable differences in behavior among different groups (e.g., individuals with different Dark Triad personality scores), but our initial attempts at capturing these differences using simple known behavioral models does not lead to significantly improved defender strategies. This suggests that richer behavioral models are needed to effectively predict and target strategies in these more complex cybersecurity game.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Decision and Game Theory for Security

ISBN

978-3-030-01553-4

ISSN

—

e-ISSN

—

Počet stran výsledku

14

Strana od-do

623-636

Název nakladatele

Springer

Místo vydání

Basel

Místo konání akce

Seattle, WS

Datum konání akce

29. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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