IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
A reachability-based access control model for online social networks
Databases and Social Networks
Primates: a privacy management system for social networks
Proceedings of the 21st ACM international conference on Information and knowledge management
| Hi-index | 0.00 |
Online social networking sites are experiencing tremendous user growth with hundreds of millions of active users. As a result, there is a tremendous amount of user profile data online, e.g., name, birthdate, etc. Protecting this data is a challenge. The task of access policy composition is a tedious and confusing effort for the average user having hundreds of friends. We propose an approach that assists users in composing and managing their access control policies. Our approach is based on a supervised learning mechanism that leverages user provided example policy settings as training sets to build classifiers that are the basis for auto-generated policies. Furthermore, we provide mechanisms to enable users to fuse policy decisions that are provided by their friends or others in the social network. These policies then regulate access to user profile objects. We implemented our approach and, through extensive experimentation, prove the accuracy of our proposed mechanisms.