Verification of data redundancy in cloud storage

Data redundancy is key to preventing data loss and achieving fault-tolerance in cloud storage. Cloud storage provider usually charges users according to the requested level of redundancy. However, a cloud provider may fail to offer the committed level of data redundancy intentionally or accidentally, but the users may not be able to detect such breach until data and economic losses have occurred. In this paper, we propose a scheme to allow users remotely assess the actually deployed data redundancy in the cloud storage without knowing the file layout information. Our layout-free scheme establishes response-time profiles for each different file placements, and uses these profiles to evaluate the level of deployed data redundancy. Our experimental results show the feasibility of our scheme on both an in-house cloud and a public cloud.

[1]  Ju Wang,et al.  Windows Azure Storage: a highly available cloud storage service with strong consistency , 2011, SOSP.

[2]  Rauno V. Alatalo,et al.  Problems in the measurement of evenness in ecology , 1981 .

[3]  Benjamin Farley,et al.  Resource-freeing attacks: improve your cloud performance (at your neighbor's expense) , 2012, CCS.

[4]  Erik Riedel,et al.  A performance study of sequential I/O on windows NT TM 4 , 1998 .

[5]  Ronald L. Rivest,et al.  How to tell if your cloud files are vulnerable to drive crashes , 2011, CCS '11.

[6]  Ronald L. Rivest,et al.  Hourglass schemes: how to prove that cloud files are encrypted , 2012, CCS.

[7]  V. Chiang,et al.  Eucalyptus , 2008, Economic Botany.

[8]  Yevgeniy Dodis,et al.  Proofs of Retrievability via Hardness Amplification , 2009, IACR Cryptol. ePrint Arch..

[9]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[10]  Hovav Shacham,et al.  Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds , 2009, CCS.

[11]  Ari Juels,et al.  New approaches to security and availability for cloud data , 2013, CACM.

[12]  Michael J. Nash,et al.  The Chinese Wall security policy , 1989, Proceedings. 1989 IEEE Symposium on Security and Privacy.

[13]  Sushil Jajodia,et al.  Disk storage isolation and verification in cloud , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[14]  Michael K. Reiter,et al.  HomeAlone: Co-residency Detection in the Cloud via Side-Channel Analysis , 2011, 2011 IEEE Symposium on Security and Privacy.

[15]  Moni Naor,et al.  The complexity of online memory checking , 2005, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05).

[16]  Hovav Shacham,et al.  Do you know where your cloud files are? , 2011, CCSW '11.

[17]  Reihaneh Safavi-Naini,et al.  LoSt: location based storage , 2012, CCSW '12.

[18]  M. Hill Diversity and Evenness: A Unifying Notation and Its Consequences , 1973 .

[19]  John Wilkes,et al.  An introduction to disk drive modeling , 1994, Computer.