TY - GEN
T1 - An economic model and simulation results of App adoption decisions on networks with interdependent privacy consequences
AU - Pu, Y.
AU - Grossklags, Jens
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - The popularity of third-party apps on social network sites and mobile networks emphasizes the problem of the interdependency of privacy. It is caused by users installing apps that often collect and potentially misuse the personal information of users’ friends who are typically not involved in the decision-making process. In this paper, we provide an economic model and simulation results addressing this problem space. We study the adoption of social apps in a network where privacy consequences are interdependent. Motivated by research in behavioral economics, we extend the model to account for users’ other-regarding preferences; that is, users care about privacy harms they inflict on their peers. We present results from two simulations utilizing an underlying scalefree network topology to investigate users’ app adoption behaviors in both the initial adoption period and the late adoption phase. The first simulation predictably shows that in the early adoption period, app adoption rates will increase when (1) the interdependent privacy harm caused by an app is lower, (2) installation cost decreases, or (3) network size increases. Surprisingly, we find from the second simulation that app rankings frequently will not accurately reflect the level of interdependent privacy harm when simultaneously considering the adoption results of multiple apps. Given that in the late adoption phase, users make their installation decisions mainly based on app rankings, the simulation results demonstrate that even rational actors who consider their peers’ wellbeing might adopt apps with significant interdependent privacy harms. Our findings complement the usable privacy and security studies which show that users install privacy-invasive apps because they are unable to identify and understand apps’ privacy consequences; however, we show that fully-informed and rational users will likely fall for privacy-invasive apps as well.
AB - The popularity of third-party apps on social network sites and mobile networks emphasizes the problem of the interdependency of privacy. It is caused by users installing apps that often collect and potentially misuse the personal information of users’ friends who are typically not involved in the decision-making process. In this paper, we provide an economic model and simulation results addressing this problem space. We study the adoption of social apps in a network where privacy consequences are interdependent. Motivated by research in behavioral economics, we extend the model to account for users’ other-regarding preferences; that is, users care about privacy harms they inflict on their peers. We present results from two simulations utilizing an underlying scalefree network topology to investigate users’ app adoption behaviors in both the initial adoption period and the late adoption phase. The first simulation predictably shows that in the early adoption period, app adoption rates will increase when (1) the interdependent privacy harm caused by an app is lower, (2) installation cost decreases, or (3) network size increases. Surprisingly, we find from the second simulation that app rankings frequently will not accurately reflect the level of interdependent privacy harm when simultaneously considering the adoption results of multiple apps. Given that in the late adoption phase, users make their installation decisions mainly based on app rankings, the simulation results demonstrate that even rational actors who consider their peers’ wellbeing might adopt apps with significant interdependent privacy harms. Our findings complement the usable privacy and security studies which show that users install privacy-invasive apps because they are unable to identify and understand apps’ privacy consequences; however, we show that fully-informed and rational users will likely fall for privacy-invasive apps as well.
KW - App adoption
KW - Economic model
KW - Interdependent privacy
KW - Mobile networks
KW - Other–regarding preferences
KW - Scale–free networks
KW - Simulation
KW - Social network sites
KW - Third–party apps
UR - http://www.scopus.com/inward/record.url?scp=84910020977&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-12601-2_14
DO - 10.1007/978-3-319-12601-2_14
M3 - Conference contribution
AN - SCOPUS:84910020977
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 246
EP - 265
BT - Decision and GameTheory for Security - 5th International Conference, GameSec 2014, Proceedings
A2 - Poovendran, Radha
A2 - Saad, Walid
PB - Springer Verlag
T2 - 5th International Conference on Decision and GameTheory for Security, GameSec 2014
Y2 - 6 November 2014 through 7 November 2014
ER -