Becoming cybercriminals: Incentives in networks with interdependent security

Aron Laszka, Galina Schwartz

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

3 Scopus citations

Abstract

We study users’ incentives to become cybercriminals when network security is interdependent. We present a game-theoretic model in which each player (i.e., network user) decides his type, honest or malicious. Honest users represent law-abiding network users, while malicious users represent cybercriminals. After deciding on their types, the users make their security choices. We will follow [29], where breach probabilities for large-scale networks are obtained from a standard interdependent security (IDS) setup. In large-scale IDS networks, the breach probability of each player becomes a function of two variables: the player’s own security action and network security, which is an aggregate characteristic of the network; network security is computed from the security actions of the individual nodes that comprise the network. This allows us to quantify user security choices in networks with IDS even when users have only very limited, aggregate information about security choices of other users of the network.

Original languageEnglish (US)
Title of host publicationDecision and Game Theory for Security - 7th International Conference, GameSec 2016, Proceedings
EditorsEmmanouil Panaousis, Milind Tambe, Tansu Alpcan, William Casey, Quanyan Zhu
PublisherSpringer Verlag
Pages349-369
Number of pages21
ISBN (Print)9783319474120
DOIs
StatePublished - 2016
Event7th International Conference on Decision and Game Theory for Security, GameSec 2016 - New York, United States
Duration: Nov 2 2016Nov 4 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9996 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Decision and Game Theory for Security, GameSec 2016
Country/TerritoryUnited States
CityNew York
Period11/2/1611/4/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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