Abstract

Big data frequently contains huge amounts of personal identifiable information and therefore the protection of user’s privacy becomes a challenge. Lots of researches had been administered on securing big data, but still limited in efficient privacy management and data sensitivity. This study designed a big data framework named Big Data-ARpM that is secured and enforces privacy and access restriction level. The internal components of Big Data-ARpM consists of six modules. Data Pre-processor which contains a data cleaning component that checks each entity of the data for conformity.

How to Cite
OLUWAFEMI, ONASHOGA S.A,, FOLORUNSO O., Akinwunmi. A Secure Big Data Framework Based on Access Restriction And Preserved Level of Privacy. Global Journal of Computer Science and Technology, [S.l.], dec. 2020. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/1983>. Date accessed: 15 aug. 2022.