Name
Abstract | ||
|---|---|---|
Privacy in social networks is a large and growing concern in recent times. It refers to various issues in a social network which include privacy of users, links, and their attributes. Each privacy component of a social network is vast and consists of various sub-problems. For example, user privacy includes multiple sub-problems like user location privacy, and user personal information privacy. This survey on privacy in social networks is intended to serve as an initial introduction and starting step to all further researchers. We present various privacy preserving models and methods include naive anonymization, perturbation, or building a complete alternative network. We show the work done by multiple researchers in the past, where social networks are stated as network graphs with users represented as nodes and friendship between users represented as links between the nodes. We study ways and mechanisms developed to protect these nodes and links in the network. We also review other systems proposed, along with all the available databases for future researchers in this area. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACCESS.2018.2822693 | IEEE ACCESS |
Keywords | Field | DocType |
Anonymization,link privacy,perturbation,user privacy | Graph,World Wide Web,Social network,Friendship,Computer science,Computer network,Personally identifiable information,User privacy,Empirical research | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Madhuri Siddula | 1 | 0 | 3.72 |
| Lijie Li | 2 | 4 | 3.84 |
| Yingshu Li | 3 | 671 | 53.71 |