Computer Science ›› 2017, Vol. 44 ›› Issue (2): 195-201.doi: 10.11896/j.issn.1002-137X.2017.02.031

Previous Articles     Next Articles

Research on MapReduce-based Data Auditing Method for Cloud Storage

JIN Yu and YAN Dong   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Cloud storage is a new network storage technology.It is an important service provided by cloud computing.Cloud storage is very popular in cloud users for its characteristics of speediness,low price and convenience.However,it also brings many security problems towards user’s outsourced data.One major problem is to ensure the integrity of data at semi-trusted cloud server.So cloud users and cloud servers are both in urgent need of a stable,safe and credible data auditing method.With the arrival of the era of big data,the efficiency of dealing with huge amounts of data in cloud by traditional data batch auditing methods is not high.What’s more,with the popularity of mobile clients,the traditional auditing methods bring too much online burden to cloud user.Therefore,this paper proposed a data auditing method based on MapReduce programming framework for cloud storage.It uses the technology of proxy signature,which deals with data signing instead of cloud user.Moreover,it can also complete the work of data signing and batch auditing in parallel.The experiment results show that the proposed method clearly improves the efficiency of batch auditing,enhances the availability of cloud storage service and reduces the online burden towards cloud user.

Key words: Cloud storage,Data auditing,MapReduce,Proxy signature

[1] LIU P.Cloud Computing (Second edition)[M].Beijing:Beijing Electronic Industry Press,2011.
[2] MELL P,GRANCE T.The NIST definition of cloud computing[J].Communications of the ACM,2011,3(6):50 .
[3] HASAN R,YURCIK W,MYAGMAR S.The evolution of sto-rage service providers:techniques and challenges to outsourcing storage[J].ACM Workshop on Storage Security & Survivability ACM,2005:1-8.
[4] MORSY M A,GRUNDY J,MLLER I.An Analysis of theCloud Computing Security Problem[C]∥Proceedings of APSEC 2010 Cloud Workshop.Sydney,Australia,2010.
[5] GIANI A,BITAR E,GARCIA M,et al.Smart Grid Data Integrity Attacks[J].IEEE Transactions on Smart Grid,2013,4(3):1244-1253.
[6] OUALHA N,LENEUTRE J,ROUDIER Y.Verifying remote data integrity in peer-to-peer data storage:A comprehensive survey of protocols[J].Peerto-Peer Networking and Applications,2012,5(3):231-243.
[7] WANG C,REN K,LOU W,et al.Toward publicly auditable secure cloud data storage services[J].Network,IEEE,2010,24(4):19-24.
[8] MAMBO M,USUDA K,OKAMOTO E.Proxy signature:delegation Of the power to sign messages[J].Ieice Transactions on Fundamentals of Electronics Communications & Computer Scien-ces,1996,79(9):1338-1354.
[9] ATENIESE G,BURNS R C,CURTMOLA R,et al.Provable data possession at untrusted stores[C]∥Proceedings of the 14th ACM Conference on Computer and Communications Secu-rity.2007:598-609.
[10] JUELS A,KALISKI JR B S.PORs:Proofs of retrievability for large files[C]∥Proceedings of the 14th ACM Conference on Computer and Communications Security.ACM,2007:584-597.
[11] ATENIESE G,DI PIETRO R,MANCINI L V,et al.Scalableand efficient provable data possession[C]∥Proceedings of the 4th International Conference on Security and Privacy in Communication Netowrks.ACM,2008:1-10.
[12] ERWAY C.Dynamic provable data possession[C]∥Proceedings of the 16th ACM Conference on Computer and Communications Security.ACM,2009:213-222.
[13] WANG C,WANG Q,REN K.Ensuring data storage security in cloud computing[C]∥17th International Workshop on Quality of Service,2009.IWQoS.2009.
[14] WANG Q,WANG C,LI J,et al.Enabling public verifiabilityand data dynamics for storage security in cloud computing[M]∥Computer Security(ESORICS 2009).Springer Berlin Heidelberg,2009:355-370.
[15] WANG C,WANG Q,REN K,et al.Privacy-preserving public auditing for data storage security in cloud computing[C]∥ 2010 Proceedings IEEE INFOCOM.2010:1-9.
[16] WANG Q,WANG C,REN K,et al.Enabling public auditability and data dynamics for storage security in cloud computing[J].IEEE Transactions on Parallel and Distributed Systems,2011,22(5):847-859.
[17] KIM S,PARK S,WON D.Proxy signatures,Revisited[J].Infor-mation and Communications Security,1997:223-232.
[18] http://wiki.apache.org/hadoop/#MapReduce.
[19] GUO Peng.Cassandra in Action.China Machine Press.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .