Scalable and efficient provable data possession

By Giuseppe Ateniese, Roberto Di Pietro, Luigi Vincenzo Mancini, Gene Tsudik. IACR Cryptology ePrint Archive, 2008

1,512 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/b3c7af3cf2322505da2327add85555a94e1c834d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Kui Ren
2. Wenjing Lou
3. Giuseppe Ateniese
4. Brent Waters
5. Seny Kamara
6. Qian Wang
7. Jonathan Katz
8. Dan Boneh

In Information Systems

1. Kui Ren
2. Wenjing Lou
3. Giuseppe Ateniese
4. Qian Wang
5. Seny Kamara
6. Jonathan Katz
7. Boyang Wang
8. Ari Juels

Citations in the corpus

• Remote data checking using provable data possession (2011, methodology): “2010], and to ef.ciently support dynamic data updates [Ateniese et al. 2008; Erway et al. 2009].”
• A Secure Erasure Code-Based Cloud Storage System with Secure Data Forwarding (2012, background): “The concept of provable data possession [20], [21] and the notion of proof of storage [22], [23], [24] are proposed.”
• HAIL: a high-availability and integrity layer for cloud storage (2009, methodology): “Subsequent work gives file update protocols in the PDP model [3, 13].”
• Privacy-Preserving Public Auditing for Secure Cloud Storage (2013, background): “In cloud computing, outsourced data might not only be accessed but also updated frequently by users for various application purposes [21], [8], [22], [23].”
• Enabling Public Verifiability and Data Dynamics for Storage Security in Cloud Computing (2009, background): “However, like [ 11 ], the number of queries a client can perform is also a fixed priori and the introduction of pre-computed “sentinels” prevents the development of realizing dynamic data updates.”
• Panda: Public Auditing for Shared Data with Efficient User Revocation in the Cloud (2015, background): “[31] presented another PDPmechanism based on symmetric keys.”
• Compact Proofs of Retrievability (2008, positive): “3 We note that the sentinel-based scheme of Juels and Kaliski [12], the scheme of Ateniese, Di Pietro, Mancini, and Tsudik [3], and the scheme of Shah, Swaminathan and Baker [17] lack both unbounded use and statelessness.”
• Privacy-Preserving Audit and Extraction of Digital Contents (2008, methodology): “For future work, we should consider modifying previous schemes [1, 2, 11, 23] to allow privacypreserving audit and extraction.”
• Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing (2010, methodology): “[21] propose a partially dynamic version of the prior PDP scheme, using only symmetric key cryptography but with a bounded number of audits.”
• Proxy Provable Data Possession in Public Clouds (2013, methodology): “In 2007, Ateniese et al. proposed the concept of provable data possession (PDP) [1].”
• Cooperative Provable Data Possession for Integrity Verification in Multicloud Storage (2012, methodology): “Various PDP schemes have been recently proposed, such as Scalable PDP [4] and Dynamic PDP [5].”
• An Efficient Public Auditing Protocol With Novel Dynamic Structure for Cloud Data (2017, background): “[28] first proposed a partially dynamic provable data possession (PDP) protocol, which represents an important step toward substantially more practical PDP techniques.”
• Dynamic provable data possession (2009, methodology): “Note that the restriction to the PDP scheme gives a security definition for PDP schemes compatible with the ones in [2, 3].”
• Ensuring data storage security in Cloud Computing (2009, methodology): “This is faster than the hash function based token pre-computatio n scheme proposed in [7].”
• Security and privacy for storage and computation in cloud computing (2014, methodology): “[3] proposed a partially dynamic version of the PDP scheme using symmetric key cryptography.”
• Dynamic Data Operations with Deduplication in Privacy-Preserving Public Auditing for Secure Cloud Storage (2017, positive): “[29] developed a partially dynamic version of the prior PDP scheme based on cryptographic hash function and symmetric key encryption.”
• A Privacy-Preserving Remote Data Integrity Checking Protocol with Data Dynamics and Public Verifiability (2011, background): “Recently, many works [1], [3], [4], [5], [6], [7], [8], [9], [13], [14], [15] focus on providing three advanced features for remote data integrity checking protocols: data dynamics [5], [6], [8], [14], public verifiability [3], [8], [9], [14], and privacy against verifiers [9], [14].”
• Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving for Cloud Storage (2017, background): “This scheme [21] is efficient but has only limited number of queries and block insertion cannot explicitly be supported.”
• Security issues in cloud environments: a survey (2014, background): “[19] acknowledged that the main issue of such checking is to verify how frequently, efficiently and securely a storage server, or a group of servers, is faithfully storing customers outsourced data, which is always under the threat of being tampered with by insiders or outsiders [257].”