A survey on Proof of Retrievability for cloud data integrity and availability: Cloud storage state-of-the-art, issues, solutions and future trends

Tan, Choon Beng; Hijazi, Mohd Hanafi Ahmad; Lim, Yuto; Gani, Abdullah

doi:10.1016/j.jnca.2018.03.017

Cited by 64 publications

(39 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to confidentiality, remote data integrity [26] is another concern for secure outsourcing storage. Accordingly, proof of data possession [27], [28] and proof of data retrievability [29], [30] were proposed to verify the cloud data integrity.…”

Section: ) Cloud Securitymentioning

confidence: 99%

Secure Data Sharing and Search for Cloud-Edge-Collaborative Storage

Tao

Jin

2020

IEEE Access

View full text Add to dashboard Cite

Cloud-edge-collaborative storage (CECS) is a promising framework to process data of the internet of things (IoT). It allows edge servers to process IoT data in real-time and stores them on a cloud server. Hence, it can rapidly respond to the requests of IoT devices, provide a massive volume of cloud storage for IoT data, and conveniently share IoT data with users. However, due to the vulnerability of edge and cloud servers, CECS suffers from the risk of data leakage. Existing secure CECS schemes are secure only if all edge servers are trusted. In other words, if any edge server is compromised, all cloud data (generated by IoT devices) will be leaked. Additionally, it is costly to request expected data from the cloud, which is linear with respect to the number of edge servers. To address the above problems, we propose a new secure data search and sharing scheme for CECS. Our scheme improves the existing secure CECS scheme in the following two ways. First, it enables users to generate a public-and-private key pair and manage private keys by themselves. In contrast, the existing solution requires edge servers to manage users' private keys. Second, it uses searchable public-key encryption to achieve more secure, efficient, and flexible data searching. In terms of security, our scheme ensures the confidentiality of cloud data and secure data sharing and searching and avoids a single point of breakthrough. In terms of performance, the experimental results show that our scheme significantly reduces users' computing costs by delegating most of the cryptographic operations to edge servers. Especially, our scheme reduces the computing and communication overhead for generating a search trapdoor compared with the existing secure CECS scheme. INDEX TERMS Cloud-edge-collaborative storage, data sharing, data search, searchable encryption.

show abstract

Section: ) Cloud Securitymentioning

confidence: 99%

Secure Data Sharing and Search for Cloud-Edge-Collaborative Storage

Tao

Jin

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…PDP [13] and PoR [14] are the two protocol mainly design for providing the data integrity in cloud storage, according to (Tan et al, 2018)PoR is more useful than the PDP though they have same functionalities because PoR can recover faulty or corrupted outsource data. Many researchers have worked on PoR with varied enhancement to it so that better integrity can be achieved, nevertheless if PoR uses with Symmetric encryption then for sure the security of data will be minimum.…”

Section: Information Integritymentioning

confidence: 99%

Research Perspective on Security Based Algorithm in Big Data Concepts

Rai,

Sharma

2020

IJEAT

View full text Add to dashboard Cite

Providing a robust security for large data is one in all the first concern for most of the researchers. This paper makes an attempt to uncover all the protection solutions associated with unstructured, structured and semi structured data. also, the main aim of this paper is to cover the information related with the several encryption algorithms used to provide confidentiality, integrity, privacy and data silos. Different algorithmic program and tools play an efficient role in playacting significant analysis on huge volume, variety of big data.

show abstract

“…Data security is one of the key challenges in the big data era [2]. In this context, securing the data in cloud computing invoked the efforts of crypt-analysts, network security experts, software security engineers, and many others, and data breaches are still occurring within cloud computing [3]. In fact, the data security issue is aggravated in the case of fog computing [4].…”

Section: Related Workmentioning

confidence: 99%

Preserving data security in distributed fog computing

et al. 2019

View full text Add to dashboard Cite

In this paper, a novel cryptographic solution is proposed to secure data in fog computing. The solution combines the AES-GMAC operation mode with information dispersal over GF(2 w) to provide data confidentiality, integrity, and availability along with source authentication. The value of w is flexible (8, 16, 32 or 64) and it could be configured according to the fog device features. Moreover, the proposed cryptographic solution is based on the dynamic key-dependent approach, which allows for a good compromise between the security level and computational complexity. In the proposed solution, the collected data at one fog node is encrypted, authenticated and dispersed in a pseudorandom manner to its n neighbor fog nodes. For data recovery, any k of the n fragments along with the corresponding dynamic key are required to retrieve the original data. This complicates the attacker's task who needs to compromise at least k fog nodes to disclose the encrypted data. Additionally, attackers should seek the dynamic key, which is different for each input data. On the other hand, redundant fragments protect the stored data against up to (n − k) fog nodes' failure or unavailability. The security and performance analysis tests show that the proposed security scheme exhibits a high level of efficiency and robustness.

show abstract

A survey on Proof of Retrievability for cloud data integrity and availability: Cloud storage state-of-the-art, issues, solutions and future trends

Cited by 64 publications

References 25 publications

Secure Data Sharing and Search for Cloud-Edge-Collaborative Storage

Secure Data Sharing and Search for Cloud-Edge-Collaborative Storage

Research Perspective on Security Based Algorithm in Big Data Concepts

Preserving data security in distributed fog computing

Contact Info

Product

Resources

About