PPSecS: Privacy-Preserving Secure Big Data Storage in a Cloud Environment

被引:4
作者
Bouleghlimat, Imene [1 ]
Boudouda, Souheila [1 ]
Hacini, Salima [1 ]
机构
[1] Univ Constantine 2 Abdelhamid Mehri, Software Technol & Informat Syst Dept, LIRE Lab, Nouvelle Ville Ali Mendjli, BP:67A, Constantine, Algeria
关键词
Big data; Data security; Cloud computing; Cryptography; Sampling;
D O I
10.1007/s13369-023-07924-4
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The proliferation of social networks, the Internet of Things, and economic mobility has led to an exponential increase in data. New data having high volume, high velocity, high variety, and high value are called big data. Big data present additional requirements in terms of storage and computation resources. Various enterprises aim to outsource their big data services to the cloud because of its cost efficiency, less management, resource pooling, and resilient computing. However, outsourcing the storage of sensitive data can expose them to potential security risks. Encryption presents a straightforward solution for data privacy preserving. In traditional encryption mechanisms, such as advanced encryption standard, the data owner and users must share an exact key for both data encryption and decryption. Currently, these mechanisms do not provide a scalable and secure solution for big data storage and analysis. Furthermore, they need to be more efficient to support big data velocity. Unfortunately, securing outsourced big data storage to a public cloud environment to later maintain efficient and secure processing over encrypted data by cloud servers cannot be ensured using traditional encryption mechanisms. In this paper, we propose a security approach for this issue by which honest but curious users or cloud service providers cannot reach complete information from the stored data. From the analysis, the proposed approach can provide secure cloud-assisted big data. Meanwhile, the performance evaluation shows the efficiency of the proposed approach.
引用
收藏
页码:3225 / 3239
页数:15
相关论文
共 50 条
[21]   Achieving Efficient and Privacy-Preserving Multi-Domain Big Data Deduplication in Cloud [J].
Yang, Xue ;
Lu, Rongxing ;
Shao, Jun ;
Tang, Xiaohu ;
Ghorbani, Ali A. .
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2021, 14 (05) :1292-1305
[22]   Lightweight and Privacy-Preserving Delegatable Proofs of Storage with Data Dynamics in Cloud Storage [J].
Yang, Anjia ;
Xu, Jia ;
Weng, Jian ;
Zhou, Jianying ;
Wong, Duncan S. .
IEEE TRANSACTIONS ON CLOUD COMPUTING, 2021, 9 (01) :212-225
[23]   Privacy-Preserving Public Auditing for Shared Data in Mobile Cloud Storage [J].
Zhao, Xia'nan ;
Wang, Dongsheng .
2022 IEEE/ACM 7TH SYMPOSIUM ON EDGE COMPUTING (SEC 2022), 2022, :486-491
[24]   Privacy-Preserving Public Auditing for Shared Cloud Data With Secure Group Management [J].
Kim, Dongmin ;
Kim, Kee Sung .
IEEE ACCESS, 2022, 10 :44212-44223
[25]   Secure Outsourcing Algorithm for Signature Generation in Privacy-Preserving Public Cloud Storage Auditing [J].
Zhao, Pu ;
Yu, Jia ;
Zhang, Hanlin .
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2019, 35 (03) :635-650
[26]   Privacy Preserving Data Aggregation on Secure Cloud [J].
Komawar, Saket ;
Batwal, Mayur ;
Shah, Shubham ;
Shahani, Snehkumar ;
Abraham, Jibi .
2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2018,
[27]   Privacy-Preserving Data Sharing in Cloud Computing [J].
王慧 .
JournalofComputerScience&Technology, 2010, 25 (03) :401-414
[28]   Privacy-Preserving Data Sharing in Cloud Computing [J].
Wang, Hui .
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2010, 25 (03) :401-414
[29]   Privacy-Preserving Ciphertext Multi-Sharing Control for Big Data Storage [J].
Liang, Kaitai ;
Susilo, Willy ;
Liu, Joseph K. .
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2015, 10 (08) :1578-1589
[30]   Privacy-Preserving Data Sharing in Cloud Computing [J].
Hui Wang .
Journal of Computer Science and Technology, 2010, 25 :401-414