Assessment of Integrity Auditing Protocols for Outsourced Big Data

Due to overwhelming advancement in sensor networks and communication technology, Internet of Things is taking shape to help make our lives smarter. Devices working on Internet of Things are responsible for generating multifarious and mammoth data. In addition to this, academia, business firms, etc., add vast amount of data to the pool of storage systems. This data are big data. Cloud computing provides paramount solution to store and process this big data through database outsourcing, thus reducing capital expenditure and operational costs. As big data are hosted by third party service providers in the cloud, security of such data becomes one of the significant concerns of data owners. The untrustworthy nature of service providers does not guarantee the security of data and computation results. This necessitates the owners to audit the integrity of data. Therefore, integrity auditing becomes the part and parcel of outsourced big data. Maintaining confidentiality, privacy, and trust for such big data are sine qua non for seamless and secure execution of big data-related applications. This paper gives a thorough analysis of integrity auditing protocols applied for big data residing in cloud environment.

[1]  Yihua Zhang,et al.  Efficient Dynamic Provable Possession of Remote Data via Update Trees , 2016, TOS.

[2]  Hovav Shacham,et al.  Compact Proofs of Retrievability , 2008, ASIACRYPT.

[3]  Fatos Xhafa,et al.  OPoR: Enabling Proof of Retrievability in Cloud Computing with Resource-Constrained Devices , 2015, IEEE Transactions on Cloud Computing.

[4]  B. Padmavathi,et al.  Survey of Confidentiality and Integrity in Outsourced Databases , 2013 .

[5]  Hong Jiang,et al.  Dynamic and Public Auditing with Fair Arbitration for Cloud Data , 2018, IEEE Transactions on Cloud Computing.

[6]  Roberto Tamassia,et al.  Dynamic provable data possession , 2009, IACR Cryptol. ePrint Arch..

[7]  Tao Jiang,et al.  Public Integrity Auditing for Shared Dynamic Cloud Data with Group User Revocation , 2016, IEEE Transactions on Computers.

[8]  Anmin Fu,et al.  NPP: A New Privacy-Aware Public Auditing Scheme for Cloud Data Sharing with Group Users , 2017, IEEE Transactions on Big Data.

[9]  Ajeet Ram Pathak,et al.  A secure threshold secret sharing framework for database outsourcing , 2014, 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies.

[10]  Ertem Esiner,et al.  FlexDPDP , 2016, ACM Trans. Storage.

[11]  David Cash,et al.  Dynamic Proofs of Retrievability Via Oblivious RAM , 2013, Journal of Cryptology.

[12]  Huaqun Wang,et al.  Identity-Based Distributed Provable Data Possession in Multicloud Storage , 2015, IEEE Transactions on Services Computing.

[13]  Gail-Joon Ahn,et al.  Cooperative Provable Data Possession for Integrity Verification in Multicloud Storage , 2012, IEEE Transactions on Parallel and Distributed Systems.

[14]  Jiankun Hu,et al.  Identity-Based Data Outsourcing With Comprehensive Auditing in Clouds , 2017, IEEE Transactions on Information Forensics and Security.

[15]  Lei Zhang,et al.  Privacy-Preserving Public Auditing Protocol for Low-Performance End Devices in Cloud , 2016, IEEE Transactions on Information Forensics and Security.

[16]  Reza Curtmola,et al.  Provable data possession at untrusted stores , 2007, CCS '07.

[17]  Ari Juels,et al.  Pors: proofs of retrievability for large files , 2007, CCS '07.