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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rohil, Mukesh Kumar | - |
dc.date.accessioned | 2022-12-27T10:41:30Z | - |
dc.date.available | 2022-12-27T10:41:30Z | - |
dc.date.issued | 2019-10 | - |
dc.identifier.uri | https://link.springer.com/chapter/10.1007/978-981-32-9949-8_21 | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8173 | - |
dc.description.abstract | Big data has opened the possibility of making great advancements in many scientific disciplines and has become a very interesting topic in academic world and in industry. It has also given contributions to innovation, improvements in productivity and competitiveness. However, at present, there are various security risks involved in the process of collection, storage and use. The leakage of privacy caused by big data poses serious problems for the users; also the incorrect or false big data may lead to wrong or invalid analysis of results. The presented work analyzes the technical challenges of implementing big data security and privacy protection, and describes some key solutions to address the issues related with big data security and privacy. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Big Data | en_US |
dc.subject | Big data analysis | en_US |
dc.subject | Big data security | en_US |
dc.subject | Privacy protection | en_US |
dc.title | Big Data Security Challenges and Preventive Solutions | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Computer Science and Information Systems |
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