A Survey on Cloud Storage Auditing Protocols

As Today�s world depends on dynamically updated data, the best way to store and update data is cloud storage service. The common issue for storing data in cloud storage is its security though every individual client holds his/her own secret key the key service has to be supportive and is effective to the customer in different situations, so key redesign of outsourcing is important. The key overhauls can be handled by some authorized inspector known as TPA (Third Party Auditor) to reduce key upgrade burden from customer. It is the responsible of TPA now, to save key upgrades and makes key updates transparent for client. In existing solutions, client has to update key by himself at periodic times which leads to problem for those who need to concentrate on their main role in the market or with the people who have limited resources. This paper encloses a survey on the key exposure problem in cloud storage is formulated where the main goal is that cloud storage settings and key updates are safely outsourced to some third party where TPA can only hold encrypted version of client secret key formalizing security model. Security proof can be analyzed and make sure that design is secure and efficient

An extensive research survey on data integrity and deduplication towards privacy in cloud storage

Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems

Hybrid Cloud-Based Privacy Preserving Clustering as Service for Enterprise Big Data

Clustering as service is being offered by many cloud service providers. It helps enterprises to learn hidden patterns and learn knowledge from large, big data generated by enterprises. Though it brings lot of value to enterprises, it also exposes the data to various security and privacy threats. Privacy preserving clustering is being proposed a solution to address this problem. But the privacy preserving clustering as outsourced service model involves too much overhead on querying user, lacks adaptivity to incremental data and involves frequent interaction between service provider and the querying user. There is also a lack of personalization to clustering by the querying user. This work “Locality Sensitive Hashing for Transformed Dataset (LSHTD)” proposes a hybrid cloud-based clustering as service model for streaming data that address the problems in the existing model such as privacy preserving k-means clustering outsourcing under multiple keys (PPCOM) and secure nearest neighbor clustering (SNNC) models, The solution combines hybrid cloud, LSHTD clustering algorithm as outsourced service model. Through experiments, the proposed solution is able is found to reduce the computation cost by 23% and communication cost by 6% and able to provide better clustering accuracy with ARI greater than 4.59% compared to existing works

Elliptic Curve Cryptography Digital Signature Algorithm For Privacy-Preserving Public Auditing For Shared Data In The Cloud

Cloud computing becomes one of the emerging technology on now a days to share and manage their data in organization , because of its forcefulness, small communication cost and everywhere environment. Privacy preservation concern in the cloud computing becomes arise several security challenges since information stored in the cloud data is easily outsourced anywhere at any time. To manage this privacy preservation in cloud computing several number of the mechanism have been proposed in earlier work to permit both data owners and public verifiers toward proficiently audit cloud information integrity without leakage information from cloud server. But major issue of the existing works becomes these methods is that unavoidably disclose secret data to free verifiers. In order to overcome this problem in this paper presents novel privacy-preserving elliptic curve digital signature cryptography methods data integrity with the purpose to maintain public auditing on shared information stored which is stored in the cloud computing database. In the proposed methods digital signature are created to each data owner in the cloud computing environment and attain data integrity confirmation for shared information between one cloud data owner to third party auditor. In our proposed data integrity Elliptic Curve Cryptography Digital Signature Algorithm, the individuality of the signer on every one chunk in shared information is reserved privately secure manner by creation elliptic curve based private key from public verifiers. Further improve accuracy of the privacy preservation for shared information in the cloud computing proposed ECCDSA perform manifold auditing tasks parallel. The experimentation results of the proposed ECCDSA based multiple data auditing task shows that higher efficiency and higher data integrity while performing auditing task, it can be compared with existing public auditing methods. DOI: 10.17762/ijritcc2321-8169.150313