| Title | Modeling and analyzing privacy-awareness social behavior network |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Han, Xu, Liu, Yanheng, Wang, Jian |
| Conference Name | IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) |
| Keywords | behavioural sciences computing, complex networks, Computational modeling, Computing Theory and Privacy, Conferences, data privacy, decision process, driving force, Habitual privacy, highly dynamical network behaviors, Human Behavior, Information theory, network evolutions, networked human society, privacy, privacy awareness, privacy disclosure behavior, privacy driven model, privacy protection, pubcrawl, Resiliency, Scalability, security, Sensitivity, Social Behavior, social behavior network, social network, Social network services, social networking (online) |
| Abstract | The increasingly networked human society requires that human beings have a clear understanding and control over the structure, nature and behavior of various social networks. There is a tendency towards privacy in the study of network evolutions because privacy disclosure behavior in the network has gradually developed into a serious concern. For this purpose, we extended information theory and proposed a brand-new concept about so-called "habitual privacy" to quantitatively analyze privacy exposure behavior and facilitate privacy computation. We emphasized that habitual privacy is an inherent property of the user and is correlated with their habitual behaviors. The widely approved driving force in recent modeling complex networks is originated from activity. Thus, we propose the privacy-driven model through synthetically considering the activity impact and habitual privacy underlying the decision process. Privacy-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the evolution of network driven by privacy. |
| DOI | 10.1109/INFCOMW.2018.8406830 |
| Citation Key | han_modeling_2018 |
Modeling and analyzing privacy-awareness social behavior network