Table 4 Comparative study of different differential privacy mechanism
From: Differential privacy: its technological prescriptive using big data
S. no | Years | Paper/work | Focus |
|---|---|---|---|
1 | 2008 | US Census Bureau [17] | Protecting patient data confidentiality and indicating driving examples |
2 | 2009 | PINQ [18] | Interactive DP which guarantees, at runtime, that inquiries adhere to a worldwide security spending plan |
3 | 2010 | Airavat model [22] | MAC + differential privacy, i.e. access control mechanisms in integration with DP |
4 | 2012 | GUPT [26] | Makes protection saving information investigation simple for security non-specialists, the expert can transfer subjective information mining projects and GUPT ensures the security of the yields |
5 | 2014 | Google’s Rappor: randomized aggregatable privacy-preserving ordinal response | For telemetry, for example, learning insights about undesirable programming commandeering clients’ settings |
6 | 2014 | Location privacy—geo-indistinguishability [25] | Ensures the client’s correct area, while permitting surmised data—normally expected to acquire a specific wanted administration—to be discharged |
7 | 2015 | For sharing historical traffic statistics | |
8 | 2015 | DP in telecommunication big data platform, VLDB 2015 [12] | Implemented three basic DP architectures in the deployed telecommunication big data platform |
9 | 2015 | Efficient e-health data release with consistency guarantee under differential privacy, 2015 [21] | Investigated e-wellbeing information discharge issue and proposed an effective and secure e-wellbeing information discharge conspire with consistency ensure under DP |
10 | 2016 | Apple’s iOS 10 [30] | DP implemented in the messaging app and search recommendations |