Name
Abstract | ||
|---|---|---|
Privacy measurement is critical to evaluate privacy risks for business, public policy and legislation. However, there is a lack of effective and practical way to quantify, measure, and evaluate privacy. In this paper, we propose three privacy indexes for privacy measurement (ranking) for social network actor model, i.e., weighted privacy index (w-PIDX), maximum privacy index (m-PIDX), and composite privacy index (c-PIDX). We also introduce a novel virtual attribute for social network actor model to describe the combined attributes' behavior. We further evaluate and demonstrate the effectiveness of these PIDXes for various user groups in different testing scenarios. Our tests and analysis show that composite privacy index, c-PIDX, is the best to measure privacy for social network actor model. A practical approach to evaluate w-PIDX, m-PIDX, and c-PIDX is also presented in the paper. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SocialCom.2013.99 | SocialCom |
Keywords | Field | DocType |
maximum privacy index,privacy risk evaluation,attribute behavior,combined attribute,privacy index,data privacy,user groups,composite privacy index,m-pidx,practical approach,legislation,public policy,privacy risk,social network actor model,w-pidx,analysis show,weighted privacy index,privacy measurement,social networking (online),c-pidx,security of data,virtual attribute | Data mining,Internet privacy,Social network,Ranking,Computer science,Computer security,Public policy,Legislation,Actor model,Information privacy,Privacy software | Conference |
Citations | PageRank | References |
3 | 0.67 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Wang | 1 | 93 | 12.91 |
| Raj Kumar Nepali | 2 | 27 | 3.55 |