Abstract
With the widespread popularity of cloud storage, a growing quantity of tenants prefer to upload their massive data to remote cloud data center for saving local cost. Due to the great market prospect, a large quantity of enterprises provide cloud storage services, which are equipped with different prices, reliability, security, and so on. Hence, outsourced data transfer has become a fundamental requirement for tenants to flexibly change cloud service providers (CSPs) to enjoy more suitable services. Nevertheless, how to guarantee the data integrity when the data are transferred from a cloud data center to another is a concern of tenants. To solve this concern, we design a new validation data structure, namely, counting Bloom filter tree (CBFT), which can be viewed as a specific binary tree based on CBF. Then, we present an efficient outsourced data transfer scheme supporting provable data deletion, in which tenants can flexibly change CSPs and transfer their outsourced data blocks from a cloud data center to another without retrieving them. At the same time, after the data are successfully transferred, tenants can validate the transferred data integrity and usability on the new cloud data center and permanently delete the transferred data from the old cloud data center. Moreover, the formal security analysis proves that our new solution can achieve all of the anticipant security goals without interaction with a third party. At last, we develop a prototype system and implement our new solution, thus providing accurate performance evaluation, which intuitively presents the high efficiency and practicality of our new solution.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Data availability statement
Data availability depends upon the request of the researchers.
Notes
Generally speaking, we assume that the elements will be equally divided into two parts according to the original order.
References
Bai P, Zhang W, Wang XA, et al. (2018) Homomorphic authentication based on rank-based merkle hash tree. In: International conference on emerging internetworking, data & web technologies, Springer, pp 841–848, https://doi.org/10.1007/978-3-319-75928-9_76
Bentajer A, Hedabou M, Abouelmehdi K et al (2019) An IBE-based design for assured deletion in cloud storage. Cryptologia 43(3):254–265. https://doi.org/10.1080/01611194.2018.1549123
Bloom BH (1970) Space/time trade-offs in hash coding with allowable errors. Commun ACM 13(7):422–426. https://doi.org/10.1145/362686.362692
Boneh D, Lipton RJ (1996) A revocable backup system. In: Proceedings of the 6th usenix security symposium, vol 10. USENIX Association, pp 91–96
Cotet CE, Deac GC, Deac CN, et al (2020) An innovative industry 4.0 cloud data transfer method for an automated waste collection system. Sustainability 12(5):1839:1–1839:15. https://doi.org/10.3390/su12051839
Deepa N, Pandiaraja P (2020) Hybrid context aware recommendation system for e-health care by merkle hash tree from cloud using evolutionary algorithm. Soft Comput 24(10):7149–7161. https://doi.org/10.1007/s00500-019-04322-7
Fan L, Cao P, Almeida J et al (2000) Summary cache: a scalable wide-area web cache sharing protocol. IEEE/ACM Trans Netw 8(3):281–293. https://doi.org/10.1109/90.851975
Guo D, Liu Y, Li X et al (2010) False negative problem of counting bloom filter. IEEE Trans Knowl Data Eng 22(5):651–664. https://doi.org/10.1109/TKDE.2009.209
Hajnal A, Nagy E, Kacsuk P et al (2018) Data migration for large scientific datasets in clouds. Azerbaijan J High Perform Comput 1:66–86
Hao F, Clarke D, Zorzo AF (2015) Deleting secret data with public verifiability. IEEE Trans Dependable Secure Comput 13(6):617–629. https://doi.org/10.1109/TDSC.2015.2423684
Kosar T, Arslan E, Ross B, et al. (2013) Storkcloud: Data transfer scheduling and optimization as a service. In: Proceedings of the 4th ACM workshop on scientific cloud computing. ACM, pp 29–36, https://doi.org/10.1145/2465848.2465855
Lim H, Lee J, Yim C (2015) Complement bloom filter for identifying true positiveness of a bloom filter. IEEE Commun Lett 19(11):1905–1908. https://doi.org/10.1109/LCOMM.2015.2478462
Liu C, Ranjan R, Yang C et al (2014) Mur-dpa: Top-down levelled multi-replica merkle hash tree based secure public auditing for dynamic big data storage on cloud. IEEE Trans Comput 64(9):2609–2622. https://doi.org/10.1109/TC.2014.2375190
Liu J, Chen S, Wang G et al (2014) Page replacement algorithm based on counting bloom filter for nand flash memory. IEEE Trans Consum Electron 60(4):636–643. https://doi.org/10.1109/TCE.2014.7027337
Liu Y, Wang XA, Cao Y, et al. (2018) Improved provable data transfer from provable data possession and deletion in cloud storage. In: International conference on intelligent networking and collaborative systems, Springer, pp 445–452, https://doi.org/10.1007/978-3-319-98557-2_40
Ni J, Lin X, Zhang K, et al. (2016) Secure outsourced data transfer with integrity verification in cloud storage. In: 2016 IEEE/CIC international conference on communications in China (ICCC), IEEE, pp 1–6, https://doi.org/10.1109/ICCChina.2016.7636866
Rao L, Zhang H, Tu T (2017) Dynamic outsourced auditing services for cloud storage based on batch-leaves-authenticated merkle hash tree. IEEE Trans Serv Comput 13(3):451–463. https://doi.org/10.1109/TSC.2017.2708116
Rottenstreich O, Kanizo Y, Keslassy I (2013) The variable-increment counting bloom filter. IEEE/ACM Trans Netw 22(4):1092–1105. https://doi.org/10.1109/TNET.2013.2272604
Sharif MHU, Datta R (2020) Cloud data transfer and secure data storage. Int J Eng Appl Sci 7(6):11–15
Tang Y, Lee PP, Lui JC et al (2012) Secure overlay cloud storage with access control and assured deletion. IEEE Trans Dependable Secure Comput 9(6):903–916. https://doi.org/10.1109/TDSC.2012.49
Wang H, He D, Fu A et al (2019) Provable data possession with outsourced data transfer. IEEE Trans Serv Comput 14(6):1929–1939. https://doi.org/10.1109/TSC.2019.2892095
Wang J, Chen X, Li J et al (2017) Towards achieving flexible and verifiable search for outsourced database in cloud computing. Futur Gener Comput Syst 67:266–275. https://doi.org/10.1016/j.future.2016.05.002
Wang Y, Tao X, Ni J et al (2018) Data integrity checking with reliable data transfer for secure cloud storage. Int J Web Grid Serv 14(1):106–121. https://doi.org/10.1504/IJWGS.2018.088396
Xue K, Chen W, Li W et al (2018) Combining data owner-side and cloud-side access control for encrypted cloud storage. IEEE Trans Inf Forensics Secur 13(8):2062–2074. https://doi.org/10.1109/TIFS.2018.2809679
Xue L, Ni J, Li Y et al (2017) Provable data transfer from provable data possession and deletion in cloud storage. Comput Standards & Inter 54:46–54. https://doi.org/10.1016/j.csi.2016.08.006
Xue L, Yu Y, Li Y et al (2019) Efficient attribute-based encryption with attribute revocation for assured data deletion. Inf Sci 479:640–650. https://doi.org/10.1016/j.ins.2018.02.015
Yang A, Xu J, Weng J et al (2018) Lightweight and privacy-preserving delegatable proofs of storage with data dynamics in cloud storage. IEEE Trans Cloud Comput 9(1):212–225. https://doi.org/10.1109/TCC.2018.2851256
Yang C, Chen X, Xiang Y (2018) Blockchain-based publicly verifiable data deletion scheme for cloud storage. J Netw Comput Appl 103:185–193. https://doi.org/10.1016/j.jnca.2017.11.011
Yang C, Wang J, Tao X, et al (2018c) Publicly verifiable data transfer and deletion scheme for cloud storage. In: International conference on information and communications security, Springer, pp 445–458, https://doi.org/10.1007/978-3-030-01950-1_26
Yang C, Tao X, Zhao F (2019) Publicly verifiable data transfer and deletion scheme for cloud storage. Int J Distrib Sens Netw 15(10):1–15. https://doi.org/10.1177/1550147719878999
Yang C, Tao X, Zhao F, et al. (2019b) A new outsourced data deletion scheme with public verifiability. In: International conference on wireless algorithms, systems, and applications, Springer, pp 631–638, https://doi.org/10.1007/978-3-030-23597-0_53
Yang C, Liu Y, Tao X (2020) Assure deletion supporting dynamic insertion for outsourced data in cloud computing. Int J Distrib Sens Netw 16(9):1–14. https://doi.org/10.1177/1550147720958294
Yang C, Liu Y, Tao X, et al. (2020b) Publicly verifiable and efficient fine-grained data deletion scheme in cloud computing. IEEE Access 8:99,393–99,403. https://doi.org/10.1109/ACCESS.2020.2997351
Yang C, Tao X, Wang S, et al. (2020c) Data integrity checking supporting reliable data migration in cloud storage. In: International conference on wireless algorithms, systems, and applications, Springer, pp 615–626, https://doi.org/10.1007/978-3-030-59016-1_51
Yang C, Tao X, Zhao F et al (2020) Secure data transfer and deletion from counting bloom filter in cloud computing. Chin J Electron 29(2):273–280. https://doi.org/10.1049/cje.2020.02.015
Yang C, Zhao F, Tao X et al (2021) Publicly verifiable outsourced data migration scheme supporting efficient integrity checking. J Netw Comput Appl. https://doi.org/10.1016/j.jnca.2021.103184
Yang Y, Zhou Y, Liang L, et al. (2010) A sevice-oriented broker for bulk data transfer in cloud computing. In: 2010 ninth international conference on grid and cloud computing, IEEE, pp 264–269, https://doi.org/10.1109/GCC.2010.60
Yu J, Wang H (2017) Strong key-exposure resilient auditing for secure cloud storage. IEEE Trans Inf Forensics Secur 12(8):1931–1940. https://doi.org/10.1109/TIFS.2017.2695449
Yu Y, Ni J, Wu W, et al (2015) Provable data possession supporting secure data transfer for cloud storage. In: 2015 10th international conference on broadband and wireless computing, communication and applications (BWCCA), IEEE, pp 38–42, https://doi.org/10.1109/BWCCA.2015.44
Yu Y, Xue L, Li Y et al (2018) Assured data deletion with fine-grained access control for fog-based industrial applications. IEEE Trans Industr Inf 14(10):4538–4547. https://doi.org/10.1109/TII.2018.2841047
Zhang Z, Tan S, Wang J, et al (2018) An associated deletion scheme for multi-copy in cloud storage. In: International conference on algorithms and architectures for parallel processing, Springer, pp 511–526, https://doi.org/10.1007/978-3-030-05063-4_38
Acknowledgements
This work is supported by Guilin University of Electronic Technology, Guilin, China. At the same time, the authors would like to sincerely thank the anonymous referees for their very valuable time.
Funding
This work is supported by the Science and Technology Program of Guangxi(Project No.: AD20297028), the Natural Science Foundation of Guangxi(Project No.: 2020GXNSFBA297132), the Guangxi Key Laboratory of Cryptography and Information Security(Project No.: GCIS202128), the National Key R& D Program of China(Project No.: 2020YFB1006003), the National Natural Science Foundation of China(Project No.: 61772150) and the Guangdong Key R &D Program(Project No.: 2020B0101090002).
Author information
Authors and Affiliations
Contributions
All of the authors contribute to this manuscript; then, the detail contributions are as follows. Changsong Yang took part in conceptualization, methodology, software, writing—original draft preparation, visualization, investigation, writing—reviewing and editing; Yueling Liu involved in data curation; Yong Ding took part in supervision.
Corresponding author
Ethics declarations
Conflict of interests
The authors declared that there is no conflict of interest. At the same time, the authors declared that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part.
Informed consent
All authors have read this manuscript and are willing to process it for publication.
Ethical approval
There is no need for ethical approval while conducting the study in this manuscript.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Yang, C., Liu, Y. & Ding, Y. Efficient data transfer supporting provable data deletion for secure cloud storage. Soft Comput 26, 6463–6479 (2022). https://doi.org/10.1007/s00500-022-07116-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-022-07116-6