Name
Abstract | ||
|---|---|---|
In the past few decades, smartphones and Global Positioning System(GPS) devices have led to the popularity of Location Based Services. It is crucial for large MNCs to get a lot of data from people and provide their services accordingly. However, on the other side, the concern of privacy has also increased among the users, and they would like to hide their whereabouts. The rise of data consumption and the hunger for faster network speed has also led to the emergence of new concepts such as the Fog Computing. Fog computing paradigm extends the storage, networking, and computing facilities of the cloud computing towards the edge of the networks while removing the load on the server centers and decreasing the latency at the edge device.The fog computing will help in unlimited growth of location services and this adoption of fog computing calls for the need for more secure and robust algorithms for location privacy. One of the ways we can alter the information regarding the location of the user is Location Obfuscation.This can be done reversibly or irreversibly. In this paper, we address the problem of location privacy and present a solution based on the type of data that has to be preserved (in our case, it is distance). A mobile application has been designed and developed to test and validate the feasibility of the proposed obfuscation techniques for the Fog computing environments. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TENCON.2019.8929236 | TENCON IEEE Region 10 Conference Proceedings |
Keywords | Field | DocType |
Data-Obfuscation,Fog-Computing,Location-Privacy,Security,Encryption | Edge computing,Computer security,Computer science,Location-based service,Encryption,Electronic engineering,Edge device,Information privacy,Obfuscation,Location awareness,Cloud computing | Conference |
ISSN | Citations | PageRank |
2159-3442 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chandan Naik | 1 | 0 | 0.34 |
| M. Siddhartha | 2 | 0 | 0.34 |
| John Paul Martin | 3 | 0 | 0.34 |
| K. Chandrasekaran | 4 | 42 | 12.16 |