Title
Enhancing Privacy in Online Social Communities: Can Trust Help Mitigate Privacy Risks?
Abstract
The context based privacy model CBPM has proved to be successful in strengthening privacy specifications in social media. It allows users to define their own contexts and specify fine-grained policies. Collective-CBPM learns the user policies from community. Our experiments on a sample collection of Facebook data demonstrated the models feasibility in real time systems. These experiments however, did not capture all of the user scenarios; in this paper we simulate users for all possible user scenarios in a social network. We operationalize the C-CBPM model and study its functional behavior. We conduct experiments on a simulated environment. Our results demonstrate that even the most conservative user never incurs risk greater than 20%. Moreover, the risk diminishes to 0 as the trust increases between donors and adopters. The model poses absolutely no risk to other liberal or semi-liberal users.
Year
DOI
Venue
2014
10.1007/978-3-319-04483-5_30
ICDCIT
Keywords
Field
DocType
context based privacy model, collective-CBPM, access control, trust, collective intelligence, social media
Internet privacy,Social media,Social network,Privacy by Design,Computer security,Collective intelligence,Computer science,Scenario,Access control,Operationalization,Information privacy
Conference
Volume
ISSN
Citations 
8337
0302-9743
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Venkata Swamy Martha1242.11
Nitin Agarwal262962.97
srini ramaswamy333745.77