Security investment under cognitive constraints

A Gestalt Nash equilibrium approach

Juntao Chen, Quanyan Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the increasing connectivity enabled by the Internet of Things (IoT), security becomes a critical concern, and the users should invest to secure their IoT applications. Due to the massive devices in the IoT network, users cannot be aware of the security policies taken by all its connected neighbors. Instead, a user makes security decisions based on the cyber risks he perceives by observing a selected number of nodes. To this end, we propose a model which incorporates the limited attention or bounded rationality nature of players in the IoT. Specifically, each individual builds a sparse cognitive network which includes the users to respond to. Based on this simplified cognitive network representation, each user then determines his security investment policy by minimizing his own real-world security cost. The bounded rational decision-makings of players and their cognitive network formations are interdependent, and thus should be addressed in a holistic manner. We propose a Gestalt Nash equilibrium (GNE) solution concept to characterize the decisions of agents. Then, we design a proximal-based iterative algorithm to compute the GNE and show its convergence. With case studies to smart home communities, the designed algorithm can successfully identify the critical users whose decisions need to be taken into account by the other users during the security investment.

Original languageEnglish (US)
Title of host publication2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538605790
DOIs
StatePublished - May 21 2018
Event52nd Annual Conference on Information Sciences and Systems, CISS 2018 - Princeton, United States
Duration: Mar 21 2018Mar 23 2018

Other

Other52nd Annual Conference on Information Sciences and Systems, CISS 2018
CountryUnited States
CityPrinceton
Period3/21/183/23/18

Fingerprint

Decision making
Internet of things
Costs

Keywords

  • Cognitive Network
  • Gestalt Nash Equilibrium
  • Internet of Things
  • Security Investment

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

Cite this

Chen, J., & Zhu, Q. (2018). Security investment under cognitive constraints: A Gestalt Nash equilibrium approach. In 2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018 (pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2018.8362263

Security investment under cognitive constraints : A Gestalt Nash equilibrium approach. / Chen, Juntao; Zhu, Quanyan.

2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, J & Zhu, Q 2018, Security investment under cognitive constraints: A Gestalt Nash equilibrium approach. in 2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018. Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 52nd Annual Conference on Information Sciences and Systems, CISS 2018, Princeton, United States, 3/21/18. https://doi.org/10.1109/CISS.2018.8362263
Chen J, Zhu Q. Security investment under cognitive constraints: A Gestalt Nash equilibrium approach. In 2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6 https://doi.org/10.1109/CISS.2018.8362263
Chen, Juntao ; Zhu, Quanyan. / Security investment under cognitive constraints : A Gestalt Nash equilibrium approach. 2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6
@inproceedings{ceadd916b9194c818626301f51bf35b4,
title = "Security investment under cognitive constraints: A Gestalt Nash equilibrium approach",
abstract = "With the increasing connectivity enabled by the Internet of Things (IoT), security becomes a critical concern, and the users should invest to secure their IoT applications. Due to the massive devices in the IoT network, users cannot be aware of the security policies taken by all its connected neighbors. Instead, a user makes security decisions based on the cyber risks he perceives by observing a selected number of nodes. To this end, we propose a model which incorporates the limited attention or bounded rationality nature of players in the IoT. Specifically, each individual builds a sparse cognitive network which includes the users to respond to. Based on this simplified cognitive network representation, each user then determines his security investment policy by minimizing his own real-world security cost. The bounded rational decision-makings of players and their cognitive network formations are interdependent, and thus should be addressed in a holistic manner. We propose a Gestalt Nash equilibrium (GNE) solution concept to characterize the decisions of agents. Then, we design a proximal-based iterative algorithm to compute the GNE and show its convergence. With case studies to smart home communities, the designed algorithm can successfully identify the critical users whose decisions need to be taken into account by the other users during the security investment.",
keywords = "Cognitive Network, Gestalt Nash Equilibrium, Internet of Things, Security Investment",
author = "Juntao Chen and Quanyan Zhu",
year = "2018",
month = "5",
day = "21",
doi = "10.1109/CISS.2018.8362263",
language = "English (US)",
pages = "1--6",
booktitle = "2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Security investment under cognitive constraints

T2 - A Gestalt Nash equilibrium approach

AU - Chen, Juntao

AU - Zhu, Quanyan

PY - 2018/5/21

Y1 - 2018/5/21

N2 - With the increasing connectivity enabled by the Internet of Things (IoT), security becomes a critical concern, and the users should invest to secure their IoT applications. Due to the massive devices in the IoT network, users cannot be aware of the security policies taken by all its connected neighbors. Instead, a user makes security decisions based on the cyber risks he perceives by observing a selected number of nodes. To this end, we propose a model which incorporates the limited attention or bounded rationality nature of players in the IoT. Specifically, each individual builds a sparse cognitive network which includes the users to respond to. Based on this simplified cognitive network representation, each user then determines his security investment policy by minimizing his own real-world security cost. The bounded rational decision-makings of players and their cognitive network formations are interdependent, and thus should be addressed in a holistic manner. We propose a Gestalt Nash equilibrium (GNE) solution concept to characterize the decisions of agents. Then, we design a proximal-based iterative algorithm to compute the GNE and show its convergence. With case studies to smart home communities, the designed algorithm can successfully identify the critical users whose decisions need to be taken into account by the other users during the security investment.

AB - With the increasing connectivity enabled by the Internet of Things (IoT), security becomes a critical concern, and the users should invest to secure their IoT applications. Due to the massive devices in the IoT network, users cannot be aware of the security policies taken by all its connected neighbors. Instead, a user makes security decisions based on the cyber risks he perceives by observing a selected number of nodes. To this end, we propose a model which incorporates the limited attention or bounded rationality nature of players in the IoT. Specifically, each individual builds a sparse cognitive network which includes the users to respond to. Based on this simplified cognitive network representation, each user then determines his security investment policy by minimizing his own real-world security cost. The bounded rational decision-makings of players and their cognitive network formations are interdependent, and thus should be addressed in a holistic manner. We propose a Gestalt Nash equilibrium (GNE) solution concept to characterize the decisions of agents. Then, we design a proximal-based iterative algorithm to compute the GNE and show its convergence. With case studies to smart home communities, the designed algorithm can successfully identify the critical users whose decisions need to be taken into account by the other users during the security investment.

KW - Cognitive Network

KW - Gestalt Nash Equilibrium

KW - Internet of Things

KW - Security Investment

UR - http://www.scopus.com/inward/record.url?scp=85048538085&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85048538085&partnerID=8YFLogxK

U2 - 10.1109/CISS.2018.8362263

DO - 10.1109/CISS.2018.8362263

M3 - Conference contribution

SP - 1

EP - 6

BT - 2018 52nd Annual Conference on Information Sciences and Systems, CISS 2018

PB - Institute of Electrical and Electronics Engineers Inc.

ER -