A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends
Big data has transformed analytics and data processing in many different industries, but securing security and privacy in distributed systems like Hadoop is still rather complex. This article gives a deep analysis of the symmetric, asymmetric, and hybrid encryption techniques applied in Hadoop to pr...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025022753 |
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| author | Youness Filaly Nisrine Berros Fatna El mendili Younes El Bouzekri EL idrissi |
| author_facet | Youness Filaly Nisrine Berros Fatna El mendili Younes El Bouzekri EL idrissi |
| author_sort | Youness Filaly |
| collection | DOAJ |
| description | Big data has transformed analytics and data processing in many different industries, but securing security and privacy in distributed systems like Hadoop is still rather complex. This article gives a deep analysis of the symmetric, asymmetric, and hybrid encryption techniques applied in Hadoop to preserve massive amounts of data. We critically analyze earlier research, underlining its advantages, flaws, and important trade-offs, specifically with reference to scalability, computing expense, and implementation complexity. Additionally, we analyze new improvements like blockchain integration and post-quantum encryption, analyzing their potential to increase Hadoop security. We find weaknesses in existing techniques via a comparative study and provide a hybrid encryption system aimed at secure and efficient data processing in Hadoop settings. Researchers and practitioners searching for scalable, privacy-preserving big data platform solutions should use this paper as a reference. |
| format | Article |
| id | doaj-art-57b5412e172a48dfa374ad30c1d2a4d5 |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-57b5412e172a48dfa374ad30c1d2a4d52025-08-20T03:08:17ZengElsevierResults in Engineering2590-12302025-09-012710620310.1016/j.rineng.2025.106203A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trendsYouness Filaly0Nisrine Berros1Fatna El mendili2Younes El Bouzekri EL idrissi3Engineering Sciences Laboratory, Ibn Tofail University, National School of Applied Sciences, Kenitra, Morocco; Corresponding author.Engineering Sciences Laboratory, Ibn Tofail University, National School of Applied Sciences, Kenitra, MoroccoImage Laboratory, Moulay Ismail University of Meknes, School of Technology, Meknes, MoroccoEngineering Sciences Laboratory, Ibn Tofail University, National School of Applied Sciences, Kenitra, MoroccoBig data has transformed analytics and data processing in many different industries, but securing security and privacy in distributed systems like Hadoop is still rather complex. This article gives a deep analysis of the symmetric, asymmetric, and hybrid encryption techniques applied in Hadoop to preserve massive amounts of data. We critically analyze earlier research, underlining its advantages, flaws, and important trade-offs, specifically with reference to scalability, computing expense, and implementation complexity. Additionally, we analyze new improvements like blockchain integration and post-quantum encryption, analyzing their potential to increase Hadoop security. We find weaknesses in existing techniques via a comparative study and provide a hybrid encryption system aimed at secure and efficient data processing in Hadoop settings. Researchers and practitioners searching for scalable, privacy-preserving big data platform solutions should use this paper as a reference.http://www.sciencedirect.com/science/article/pii/S2590123025022753Big dataHadoopHadoop DFSData securityEncryptionCryptography |
| spellingShingle | Youness Filaly Nisrine Berros Fatna El mendili Younes El Bouzekri EL idrissi A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends Results in Engineering Big data Hadoop Hadoop DFS Data security Encryption Cryptography |
| title | A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends |
| title_full | A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends |
| title_fullStr | A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends |
| title_full_unstemmed | A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends |
| title_short | A comprehensive survey on big data privacy and Hadoop security: Insights into encryption mechanisms and emerging trends |
| title_sort | comprehensive survey on big data privacy and hadoop security insights into encryption mechanisms and emerging trends |
| topic | Big data Hadoop Hadoop DFS Data security Encryption Cryptography |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025022753 |
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