File(s) under permanent embargo
Privacy as a service in social network communications
conference contribution
posted on 2023-05-23, 12:07 authored by Vidyalakshmi, BS, Wong, RK, Ghanavati, M, Chi, CWith dispersing of information on social networks - both personally identifiable and general - comes the risk of these information falling into wrong hands. Users are burdened with setting privacy of multiple social networks, each with growing number of privacy settings. Exponential growth of applications (App) running on social networks have made privacy control increasingly difficult. This necessitates Privacy as a service model, especially for social networks, to handle privacy across multiple applications and platforms. Privacy aware information dispersal involves knowing who is receiving what information of ours. Our proposed service employs a supervised learning model to assist user in spotting unintended audience for a post. Different from previous work, we combine both Tie-strength and Context of the information as features in learning. Our evaluation using several classification techniques shows that the proposed method is effective and better than methods using either only Tie-strength or only Context of the information for classification.
History
Publication title
Proceedings of 2014 IEEE International Conference on Services ComputingEditors
E Ferrari, R Kaliappa, P HungPagination
456-463ISBN
978-1-4799-5066-9Department/School
School of Information and Communication TechnologyPublisher
IEEEPlace of publication
Piscataway, United StatesEvent title
2014 IEEE International Conference on Services ComputingEvent Venue
Anchorage, AlaskaDate of Event (Start Date)
2014-06-27Date of Event (End Date)
2014-07-02Rights statement
Copyright 2014 IEEERepository Status
- Restricted