Dynamic data auditing scheme for big data storage

doi:10.1007/s11704-018-8117-6

Front. Comput. Sci.

2020, Vol. 14

Issue (1) : 219-229 https://doi.org/10.1007/s11704-018-8117-6

RESEARCH ARTICLE

Dynamic data auditing scheme for big data storage

Xingyue CHEN¹, Tao SHANG², Feng ZHANG², Jianwei LIU², Zhenyu GUAN²(

)

¹. School of Electronic and Information Engineering, Beihang University, Beijing 100083, China
². School of Cyber Science and Technology, Beihang University, Beijing 100083, China

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Abstract

When users store data in big data platforms, the integrity of outsourced data is a major concern for data owners due to the lack of direct control over the data. However, the existing remote data auditing schemes for big data platforms are only applicable to static data. In order to verify the integrity of dynamic data in a Hadoop big data platform, we presents a dynamic auditing scheme meeting the special requirement of Hadoop. Concretely, a new data structure, namely Data Block Index Table, is designed to support dynamic data operations on HDFS (Hadoop distributed file system), including appending, inserting, deleting, and modifying. Then combined with the MapReduce framework, a dynamic auditing algorithm is designed to audit the data on HDFS concurrently. Analysis shows that the proposed scheme is secure enough to resist forge attack, replace attack and replay attack on big data platform. It is also efficient in both computation and communication.

Keywords big data data security remote data auditing dynamic update privacy protection

Corresponding Author(s): Zhenyu GUAN

Just Accepted Date: 06 September 2018 Online First Date: 26 February 2019 Issue Date: 24 September 2019

Cite this article:

Xingyue CHEN,Tao SHANG,Feng ZHANG, et al. Dynamic data auditing scheme for big data storage[J]. Front. Comput. Sci., 2020, 14(1): 219-229.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-018-8117-6
https://academic.hep.com.cn/fcs/EN/Y2020/V14/I1/219

1	R Chaudhary, G S Aujla, S Garg, N Kumar, J Rodrigues. SDN-enabled multi-attribute-based secure communication for smart grid in IIoT environment. IEEE Transactions on Industrial Informatics, 2018, 14(6): 2629–2640 https://doi.org/10.1109/TII.2018.2789442
2	R Chaudhary, G S Aujla, N Kumar, J Rodrigues. Optimized big data management across multi-cloud data centers: software-definednetwork-based analysis. IEEE Communications Magazine, 2018, 56(2): 118–126 https://doi.org/10.1109/MCOM.2018.1700211
3	G Ateniese, R Burns, R Curtmola, J Herring, L Kissner, Z Peterson, D Song. Provable data possession at untrusted stores. In: Proceedings of the 14th ACM Conference on Computer and Communications Security. 2007, 598–609 https://doi.org/10.1145/1315245.1315318
4	G Ateniese, R D Pietro, L V Mancini, G Tsudik. Scalable and efficient provable data possession. In: Proceedings of the 4th International Conference on Security and Privacy in Communication Networks Conference. 2008
5	A Juels, B S Kaliski. PORS: proofs of retrievability for large files. In: Proceedings of the 14th ACM Conference on Computer and Communication Security Conference. 2007, 584–597 https://doi.org/10.1145/1315245.1315317
6	H Shacham, B Waters. Compact proofs of retrievability. In: Proceedings of the 14th International Conference on the Theory and Application of Cryptology and Information Security. 2008, 90–107 https://doi.org/10.1007/978-3-540-89255-7_7
7	C Erway, A Kupcu, C Papamanthou, R Tamassia. Dynamic provable data possession. In: Proceedings of the 16th ACM Conference on Computer Communication Security. 2009, 213–222 https://doi.org/10.1145/1653662.1653688
8	Q Wang, C Wang, J Li, K Ren, W Lou. Enabling public verifiability and data dynamics for storage security in cloud computing. In: Proceedings of European Symposium on Research in Computer Security. 2009, 355–370 https://doi.org/10.1007/978-3-642-04444-1_22
9	C Wang, Q Wang, K Ren, W Lou. Privacy-preserving public auditing for data storage security in cloud computing. In: Proceedings of the 29th Conference on Information Communications. 2010, 1–9 https://doi.org/10.1109/INFCOM.2010.5462173
10	Q Wang, C Wang, K Ren, W Lou, J Li. Enabling public auditability and data dynamics for storage security in cloud computing. IEEE Transactions on Parallel and Distributed Systems, 2011, 22(5): 847–859 https://doi.org/10.1109/TPDS.2010.183
11	Y Zhu, H Hu, G J Ahn, M Yu. Cooperative provable data possession for integrity verification in multi-cloud storage. IEEE Transactions on Parallel and Distributed Systems, 2012, 23(12): 2231–2243 https://doi.org/10.1109/TPDS.2012.66
12	Y Zhu, G J Ahn, H Hu, S S Yau, H G An, C J Hu. Dynamic audit services for outsourced storages in clouds. IEEE Transactions on Services Computing, 2012, 6(2): 227–238
13	J Li, D Xie, Z Cai. Secure auditing and deduplicating data in cloud. IEEE Transactions on Computers, 2016, 65(8): 2386–2396 https://doi.org/10.1109/TC.2015.2389960
14	M Sookhak, A Akhunzada, A Gani, M K Khan, N B Anuar. Towards dynamic remote data auditing in computational clouds. The Scientific World Journal, 2014, 2014: 269357
15	K Yang, X Jia. An efficient and secure dynamic auditing protocol for data storage in cloud computing. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(9): 1717–1726 https://doi.org/10.1109/TPDS.2012.278
16	G S Aujla, R Chaudhary, N Kumar, A K Das, J Rodrigues. SecSVA: secure storage, verification, and auditing of big data in the cloud environment. IEEE Communications Magazine, 2018, 56(1): 78–85 https://doi.org/10.1109/MCOM.2018.1700379
17	N Garg, S Bawa. RITS-MHT: relative indexed and time stamped Merkle hash tree based data auditing protocol for cloud computing. Journal of Network and Computer Applications, 2017, 84: 1–13 https://doi.org/10.1016/j.jnca.2017.02.005
18	X Chen, J Li, J Weng, J Ma, W Lou. Verifiable computation over large database with incremental updates. IEEE Transactions on Computers, 2016, 65(10): 3184–3195 https://doi.org/10.1109/TC.2015.2512870
19	X Chen, J Li, X Huang, J Ma, W Lou. New publicly verifiable databases with efficient updates. IEEE Transactions on Dependable and Secure Computing, 2015, 12(5): 546–556 https://doi.org/10.1109/TDSC.2014.2366471

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