A New Framework Approach Enhances Security to Efficient Remote Collaboration in TPA Scheme for Cloud Storage

Cloud computing provides customers with storage as a service, allowing data to be stored, managed, and cached remotely. Users can also access it online. A major concern for users is the integrity of the data stored in the cloud, as it is possible for external invaders or criminals to attack, repair, or destroy the data stored in the cloud. Data auditing is a trending concept that involves hiring a third-party auditor to perform a data integrity test (TPA). The main purpose of this project is to provide a safe and effective testing system that combines features such as data integrity, confidentiality, and privacy protection. The cloud server is only used to store encrypted data blocks in the proposed system. It is not subject to any additional computer verification. TPA and the data owner are in charge of all the functions of the scheme. A variety of materials are used to evaluate the proposed audit process. The proposed solution meets all the processes while minimizing the load on cloud servers. Data dynamics actions such as data review, deletion, and installation will be performed in the future. Keywords: Cloud storage; Third Party Auditor; Public Auditing; Privacy Preserving; Integrity;

Assessing data accuracy in a large multi-institutional quality improvement registry: an update from the Pediatric Cardiac Critical Care Consortium (PC4)

Background: The Pediatric Cardiac Critical Care Consortium (PC4) is a multi-institutional quality improvement registry focused on the care delivered in the cardiac ICU for patients with CHD and acquired heart disease. To assess data quality, a rigorous procedure of data auditing has been in place since the inception of the consortium. Materials and methods: This report describes the data auditing process and quantifies the audit results for the initial 39 audits that took place after the transition from version one to version two of the registry’s database. Results: In total, 2219 total encounters were audited for an average of 57 encounters per site. The overall data accuracy rate across all sites was 99.4%, with a major discrepancy rate of 0.52%. A passing score is based on an overall accuracy of >97% (achieved by all sites) and a major discrepancy rate of <1.5% (achieved by 38 of 39 sites, with 35 of 39 sites having a major discrepancy rate of <1%). Fields with the highest discrepancy rates included arrhythmia type, cardiac arrest count, and current surgical status. Conclusions: The extensive PC4 auditing process, including initial and routinely scheduled follow-up audits of every participating site, demonstrates an extremely high level of accuracy across a broad array of audited fields and supports the continued use of consortium data to identify best practices in paediatric cardiac critical care.

Remote Data Possession Checking Scheme with Supporting Efficient Group User Authority Management for Shared Cloud Data

Under the shared big data environment, most of the existing data auditing schemes rarely consider the authorization management of group users. Meanwhile, how to deal with the shared data integrity is a problem that needs to be pondered. Thus, in this paper, we propose a novel remote data checking possession scheme which achieves group authority management while completing the public auditing. To perform authority management work, we introduce a trusted entity – group manager. We formalize a new algebraic structure operator named authorization invisible authenticator (AIA). Meanwhile, we provide two versions of AIA scheme: basic AIA scheme and standard AIA scheme. The standard AIA scheme is constructed based on the basic AIA scheme and user information table (UIT), with advanced security and wider applicable scenarios. By virtue of standard AIA scheme, the group manager can perfectly and easily carry out authority management, including enrolling, revoking, updating. On the basis of the above, we further design a public auditing scheme for non-revoked users’ shared data. The scheme is based on identity-based encryption (IBE), which greatly reduce the necessary certificate management cost. Furthermore, the detailed security analysis and performance evaluation demonstrate that the scheme is safe and feasible.

Effectiveness of data auditing as a tool to reinforce good research data management (RDM) practice: a Singapore study

Background Institutions, funding agencies and publishers are placing increasing emphasis on good research data management (RDM). RDM lapses in medical science can result in questionable data and cause the public’s confidence in the scientific community to crumble. A fledgling medical school in a young university in Singapore has mandated every funded research project to have a data management plan (DMP). However, researchers’ adherence to their DMPs was unknown until the school embarked on routine data auditing. We hypothesize that research data auditing improves RDM awareness, compliance and reception in the school. Methods We conducted surveys with research PIs and researchers before and after data auditing to evaluate differences in self-reported RDM awareness, compliance and reception. As it is mandatory to deposit research data in a central data repository system in the school, we tracked data deposition by each laboratory from 2 weeks before to 3 months after data auditing as a marker of actual RDM compliance. Results Research data auditing had an overall positive effect on self-reported RDM awareness, compliance and reception for both research PIs and researchers. Research PIs agreed more that RDM was important to scientific reproducibility, were more aware of proper RDM, had higher RDM strength in their laboratories and were more compliant with the DMP. Both research PIs and researchers believed data auditing helped them to be more compliant with data deposition in the repository. However, data auditing had no significant impact on laboratories’ data deposition rates over time, which could be due to the short sampling period. Conclusions Research PIs and researchers generally felt that data auditing was effective in improving RDM practices. It helped to evaluate their RDM practices objectively, propose corrective actions for RDM lapses and spread awareness of the university’s data management policies. Our findings corroborated other studies in medical research, geosciences, engineering and ethics that data auditing promotes good RDM practices. Hence, we recommend research institutions worldwide to adopt data auditing as a tool to reinforce research integrity.