Effective Data Storage and Dynamic Data Auditing Scheme for Providing Distributed Services in Federated Cloud

Abstract

Recently, many organizations and industries are using the cloud computing technologies for exchanging the resources and their confidential data. For this purpose, many cloud services are available and also provide the facility to categorize their users as private and public users for accessing their own data from private cloud and public cloud. The combination of these two clouds is called federated cloud which facilitates to allow both kinds of cloud users for accessing their own data on same cloud database. In this scenario, the authorization and authentication process is becoming complex task on cloud. For providing the facility to access their own data only from federated cloud, a new secured data storage and retrieval algorithm called AES and Triple-DES-based Secured Storage and Retrieval Algorithm (ATDSRA) are proposed for storing the private and public cloud user’s data securely on cloud database. Here, the TDES is used for encrypting the input data, data merging and aggregation methods were used for grouping the encrypted input data. Moreover, a new dynamic data auditing scheme called CRT-based Dynamic Data Auditing Algorithm (CRTDDA) is proposed for conducting the cloud data auditing over the federated cloud and also restricting the data access. The proposed new auditing mechanism that is able to protect the stored data from access violence. In addition, the standard Table64 is used for encryption and decryption processes. The experimental results of this work proves the efficiency of the proposed model in terms of security level.

Internet + Cloud Audit Mode in Enterprise Human Resource Audit Practice

“…This paper adopts functional analysis method to study the practical effect of Internet + cloud audit mode on enterprise human resource audit in view of the specific functions of cloud audit mode [9][10].…”

An Efficient Hybrid Job Scheduling Optimization (EHJSO) approach to enhance resource search using Cuckoo and Grey Wolf Job Optimization for cloud environment

“…A. Sermakani [31] put out an idea for a method of load balancing and scheduling that ignored the sizes of individual jobs. The author took into account the server's refresh times when processing queries.…”

Study and Analysis of Various Cloud Security, Authentication, and Data Storage Models

“…In this method, a boot password was employed for solving traditional data encryption in key management and preservation. Sermakani & Paulraj, (2020) developed a data auditing and data storage approach for data security in cloud computing. The retrieval approach and secure data storage scheme, named Advanced encryption standard and Triple Data encryption standard-based Secured Storage and Retrieval Algorithm (ATDSRA) was developed to accumulate public and private cloud user's on cloud dataset.…”

“…Computational complexity (Yang & Jia, 2012;Namasudra & Roy 2017;Peng et al, 2020) Computational time (Halabi & Bellaiche 2018;Varadharajan & Tupakula, 2014;Li et al, 2017;Megouache et al, 2020;Falmari & Brindha, 2020;Mohamed et al, 2012;Chadwick et al, 2020;GR & Reddy, 2012;Namasudra, 2019;Sermakani & Paulraj, 2020) Communication cost (Zhou et al, 2019;Megouache et al, 2020;Yang & Jia, 2012;Namasudra & Roy 2017;Han et al, 2013;Singh & Pasupuleti, 2016) Precision (Chang & Ramachandran, 2015) Encryption time (Namasudra et al, 2020;Arora et al, 2013;Shahid et al, 2020) Decryption time (Arora et al, 2013;Shahid et al, 2020) Throughput (Ismail & Islam, 2020;Tahir et al, 2020) Recall (Chang & Ramachandran, 2015) Response time (Wang et al, 2010;Varadharajan & Tupakula, 2014;Megouache et al, 2020;Chadwick et al, 2020) Mean absolute error (Lei et al, 2020;Chadwick et al, 2020) F-measure (Chang & Ramachandran, 2015) Root mean square error (Lei et al, 2020;Jaidhar, 2013) Accuracy (Halabi & Bellaiche 2018;Modic et al, 2016;…”

“…50% -59% (Li et al, 2017;Sermakani & Paulraj, 2020) 60% -69% (Varadharajan & Tupakula, 2014;Falmari & Brindha, 2020) 70% -79% (Halabi & Bellaiche 2018;Chadwick et al, 2020;Namasudra, 2019) 80% -89% (Mohamed et al, 2012;GR & Reddy, 2012) 90% -99% (Megouache et al, 2020) clearly recognized that authentication-based technique was mostly employed approach in analyzed research papers. Similarly, the Amazon access sample database was a frequently used dataset in existing papers and JAVA language was the most frequently employed software in most of the research papers.…”