Big Data Source Location Privacy and Access Control in the Framework of IoT
| Title | Big Data Source Location Privacy and Access Control in the Framework of IoT |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Zebboudj, S., Brahami, R., Mouzaia, C., Abbas, C., Boussaid, N., Omar, M. |
| Conference Name | 2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B) |
| Keywords | Access Control, Big Data, big data privacy, big data source location privacy, cryptography, Data models, data privacy, Encryption, generator objects, human factors, Internet of Things, IoT, Location, Metrics, mobile devices, policy, privacy, Protocols, pubcrawl, Resiliency, Scalability, security, Servers |
| Abstract | In the recent years, we have observed the development of several connected and mobile devices intended for daily use. This development has come with many risks that might not be perceived by the users. These threats are compromising when an unauthorized entity has access to private big data generated through the user objects in the Internet of Things. In the literature, many solutions have been proposed in order to protect the big data, but the security remains a challenging issue. This work is carried out with the aim to provide a solution to the access control to the big data and securing the localization of their generator objects. The proposed models are based on Attribute Based Encryption, CHORD protocol and $m$TESLA. Through simulations, we compare our solutions to concurrent protocols and we show its efficiency in terms of relevant criteria. |
| URL | http://ieeexplore.ieee.org/document/8192169/ |
| DOI | 10.1109/ICEE-B.2017.8192169 |
| Citation Key | zebboudj_big_2017 |