Minimizing Expected Intrusion Detection Time in Adversarial
Patrolling

D 2022

Minimizing Expected Intrusion Detection Time in Adversarial Patrolling

KLAŠKA, David, Antonín KUČERA, Vít MUSIL and Vojtěch ŘEHÁK

Basic information

Original name

Minimizing Expected Intrusion Detection Time in Adversarial Patrolling

Authors

KLAŠKA, David (203 Czech Republic, belonging to the institution), Antonín KUČERA (203 Czech Republic, guarantor, belonging to the institution), Vít MUSIL (203 Czech Republic, belonging to the institution) and Vojtěch ŘEHÁK (203 Czech Republic, belonging to the institution)

Edition

Neuveden, 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022. p. 1660-1662, 3 pp. 2022

Publisher

International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

Paper URL

RIV identification code

RIV/00216224:14330/22:00126563

Organization unit

Faculty of Informatics

ISBN

978-1-4503-9213-6

ISSN

DOI

http://dx.doi.org/10.5555/3535850.3536068

Keywords in English

Security Games; Adversarial Patrolling

Abstract

V originále

In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker’s utility is traditionally defined as the probability of completing an attack, possibly weighted by target costs. However, in many real-world scenarios, the actual damage caused by the Attacker depends on the time elapsed since the attack’s initiation to its detection. We introduce a formal model for such scenarios, and we show that the Defender always has an optimal strategy achieving maximal protection. We also prove that finite-memory Defender’s strategies are sufficient for achieving protection arbitrarily close to the optimum. Then, we design an efficient strategy synthesis algorithm based on differentiable programming and gradient descent.We evaluate the efficiency of our method experimentally.

Links

CZ.02.2.69/0.0/0.0/18_053/0016952, interní kód MU
(CEP code: EF18_053/0016952)

Name: Postdoc2MUNI

Investor: Ministry of Education, Youth and Sports of the CR, Priority axis 2: Development of universities and human resources for research and development

EF18_053/0016952, research and development project

Name: Postdoc2MUNI

MUNI/A/1145/2021, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace XI. (Acronym: SV-FI MAV XI.)

Investor: Masaryk University

0011629866, interní kód MU

Name: Models, Algorithms, and Tools for Solving Adversarial Security Problems

Investor: Ostatní - foreign

Citovat

KLAŠKA, David, Antonín KUČERA, Vít MUSIL and Vojtěch ŘEHÁK. Minimizing Expected Intrusion Detection Time in Adversarial Patrolling. Online. In Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, Matthew E. Taylor. 21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022. Neuveden: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2022, p. 1660-1662. ISBN 978-1-4503-9213-6. Available from: https://dx.doi.org/10.5555/3535850.3536068.

@inproceedings{2214539,
   author = {Klaška, David and Kučera, Antonín and Musil, Vít and Řehák, Vojtěch},
   address = {Neuveden},
   booktitle = {21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022.},
   doi = {http://dx.doi.org/10.5555/3535850.3536068},
   editor = {Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, Matthew E. Taylor},
   keywords = {Security Games; Adversarial Patrolling},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-1-4503-9213-6},
   pages = {1660-1662},
   publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
   title = {Minimizing Expected Intrusion Detection Time in Adversarial Patrolling},
   url = {https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf},
   year = {2022}
}

TY  - JOUR
ID  - 2214539
AU  - Klaška, David - Kučera, Antonín - Musil, Vít - Řehák, Vojtěch
PY  - 2022
TI  - Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
PB  - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
CY  - Neuveden
SN  - 9781450392136
KW  - Security Games
KW  - Adversarial Patrolling
UR  - https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf
N2  - In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker’s utility is traditionally defined as the probability of completing an attack, possibly weighted by target costs. However, in many real-world scenarios, the actual damage caused by the Attacker depends on the time elapsed since the attack’s initiation to its detection. We introduce a formal model for such scenarios, and we show that the Defender always has an optimal strategy achieving maximal protection. We also prove that finite-memory Defender’s strategies are sufficient for achieving protection arbitrarily close to the optimum. Then, we design an efficient strategy synthesis algorithm based on differentiable programming and gradient descent.We evaluate the efficiency of our method experimentally.
ER  -

KLAŠKA, David, Antonín KUČERA, Vít MUSIL and Vojtěch ŘEHÁK. Minimizing Expected Intrusion Detection Time in Adversarial Patrolling. Online. In Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, Matthew E. Taylor. \textit{21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022.}. Neuveden: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2022, p.~1660-1662. ISBN~978-1-4503-9213-6. Available from: https://dx.doi.org/10.5555/3535850.3536068.

Detailed Information on Publication Record