Tackling Sequential Attacks in Security Games

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00339901" target="_blank" >RIV/68407700:21230/19:00339901 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-32430-8_20" target="_blank" >https://doi.org/10.1007/978-3-030-32430-8_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-32430-8_20" target="_blank" >10.1007/978-3-030-32430-8_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Tackling Sequential Attacks in Security Games

Popis výsledku v původním jazyce

Many real-world security problems exhibit the challenge of sequential attacks (i.e., the attacker carries out multiple attacks in a sequential manner) on important targets. Security agencies have to dynamically allocate limited security resources to the targets in response to these attacks, upon receiving real-time observations regarding them. This paper focuses on tackling sequential attacks using Stackelberg security games (SSGs), a well-known class of leader-follower games, which have been applied for solving many real-world security problems. Previous work on SSGs mainly considers a myopic attacker who attacks one or multiple targets simultaneously against each defense strategy. This paper introduces a new sequential-attack game model (built upon the Stackelberg game model), which incorporates real-time observations, the behavior of sequential attacks, and strategic plans of non-myopic players. Based on the new game model, we propose practical game-theoretic algorithms for computing an equilibrium in different game settings. Our new algorithms exploit intrinsic properties of the equilibrium to derive compact representations of both game state history and strategy spaces of players (which are exponential in number in the original representations). Finally, our computational experiments quantify benefits and losses to the attacker and defender in the presence of sequential attacks.

Název v anglickém jazyce

Tackling Sequential Attacks in Security Games

Popis výsledku anglicky

Many real-world security problems exhibit the challenge of sequential attacks (i.e., the attacker carries out multiple attacks in a sequential manner) on important targets. Security agencies have to dynamically allocate limited security resources to the targets in response to these attacks, upon receiving real-time observations regarding them. This paper focuses on tackling sequential attacks using Stackelberg security games (SSGs), a well-known class of leader-follower games, which have been applied for solving many real-world security problems. Previous work on SSGs mainly considers a myopic attacker who attacks one or multiple targets simultaneously against each defense strategy. This paper introduces a new sequential-attack game model (built upon the Stackelberg game model), which incorporates real-time observations, the behavior of sequential attacks, and strategic plans of non-myopic players. Based on the new game model, we propose practical game-theoretic algorithms for computing an equilibrium in different game settings. Our new algorithms exploit intrinsic properties of the equilibrium to derive compact representations of both game state history and strategy spaces of players (which are exponential in number in the original representations). Finally, our computational experiments quantify benefits and losses to the attacker and defender in the presence of sequential attacks.

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

<a href="/cs/project/GJ19-24384Y" target="_blank" >GJ19-24384Y: Výpočet rovnovážných strategií v dynamických hrách</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

9783030324292

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

21

Strana od-do

331-351

Název nakladatele

Springer

Místo vydání

Wien

Místo konání akce

Stockholm

Datum konání akce

30. 10. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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