A data preparation approach for cloud storage based on containerized parallel patterns

In this paper, we present the design, implementation, and evaluation of an efficient data preparation and retrieval approach for cloud storage. The approach includes a deduplication subsystem that indexes the hash of each content to identify duplicated data. As a consequence, avoiding duplicated content reduces reprocessing time during uploads and other costs related to outsource data management tasks. Our proposed data preparation scheme enables organizations to add properties such as security, reliability, and cost-efficiency to their contents before sending them to the cloud. It also creates recovery schemes for organizations to share preprocessed contents with partners and end-users. The approach also includes an engine that encapsulates preprocessing applications into virtual containers (VCs) to create parallel patterns that improve the efficiency of data preparation retrieval process. In a study case, real repositories of satellite images, and organizational files were prepared to be migrated to the cloud by using processes such as compression, encryption, encoding for fault tolerance, and access control. The experimental evaluation revealed the feasibility of using a data preparation approach for organizations to mitigate risks that still could arise in the cloud. It also revealed the efficiency of the deduplication process to reduce data preparation tasks and the efficacy of parallel patterns to improve the end-user service experience.This research was supported by "Fondo Sectorial de Investigación para la Educación";, SEP-CONACyT Mexico, through projects 281565 and 285276

A federated content distribution system to build health data synchronization services

In organizational environments, such as in hospitals, data have to be processed, preserved, and shared with other organizations in a cost-efficient manner. Moreover, organizations have to accomplish different mandatory non-functional requirements imposed by the laws, protocols, and norms of each country. In this context, this paper presents a Federated Content Distribution System to build infrastructure-agnostic health data synchronization services. In this federation, each hospital manages local and federated services based on a pub/sub model. The local services manage users and contents (i.e., medical imagery) inside the hospital, whereas federated services allow the cooperation of different hospitals sharing resources and data. Data preparation schemes were implemented to add non-functional requirements to data. Moreover, data published in the content distribution system are automatically synchronized to all users subscribed to the catalog where the content was published.This work has been partially supported by the grant “CABAHLA-CM: Convergencia Big data-Hpc: de Los sensores a las Aplicaciones” (Ref: S2018/TCS-4423) of Madrid Regional Government; the Spanish Ministry of Science and Innovation Project ” New Data Intensive Computing Methods for High-End and Edge Computing Platforms (DECIDE)”. Ref. PID2019-107858GB-I00; and by the project 41756 “Plataforma tecnológica para la gestión, aseguramiento, intercambio y preservación de grandes volúmenes de datos en salud y construcción de un repositorio nacional de servicios de análisis de datos de salud” by the FORDECYT-PRONACES

Secure server-aided data sharing clique with attestation

National Research Foundation (NRF) Singapor

On the continuous processing of health data in edge-fog-cloud computing by using micro/nanoservice composition

The edge, the fog, the cloud, and even the end-user's devices play a key role in the management of the health sensitive content/data lifecycle. However, the creation and management of solutions including multiple applications executed by multiple users in multiple environments (edge, the fog, and the cloud) to process multiple health repositories that, at the same time, fulfilling non-functional requirements (NFRs) represents a complex challenge for health care organizations. This paper presents the design, development, and implementation of an architectural model to create, on-demand, edge-fog-cloud processing structures to continuously handle big health data and, at the same time, to execute services for fulfilling NFRs. In this model, constructive and modular $blocks$ , implemented as microservices and nanoservices, are recursively interconnected to create edge-fog-cloud processing structures as ¿This work was supported in part by the Council for Science and Technology of Mexico (CONACYT) through the Basic Scientific Research under Grant 2016-01-285276, and in part by the Project CABAHLA-CM: Convergencia Big data-Hpc: de los sensores a las Aplicaciones from Madrid Regional Government under Grant S2018/TCS-4423

an improved authentication scheme for remote data access and sharing over cloud storage in cyber physical social systems

n/

Security Strategies for Hosting Sensitive Information in the Commercial Cloud

IT experts often struggle to find strategies to secure data on the cloud. Although current security standards might provide cloud compliance, they fail to offer guarantees of security assurance. The purpose of this qualitative case study was to explore the strategies used by IT security managers to host sensitive information in the commercial cloud. The study\u27s population consisted of information security managers from a government agency in the eastern region of the United States. The routine active theory, developed by Cohen and Felson, was used as the conceptual framework for the study. The data collection process included IT security manager interviews (n = 7), organizational documents and procedures (n = 14), and direct observation of a training meeting (n = 35). Data collection from organizational data and observational data were summarized. Coding from the interviews and member checking were triangulated with organizational documents and observational data/field notes to produce major and minor themes. Through methodological triangulation, 5 major themes emerged from the data analysis: avoiding social engineering vulnerabilities, avoiding weak encryption, maintaining customer trust, training to create a cloud security culture, and developing sufficient policies. The findings of this study may benefit information security managers by enhancing their information security practices to better protect their organization\u27s information that is stored in the commercial cloud. Improved information security practices may contribute to social change by providing by proving customers a lesser amount of risk of having their identity or data stolen from internal and external thieve

Secure and efficient data-sharing in clouds

Cloud storage allows users to access and store data in clouds over the internet, and provides a cheap and reliable solution for users with the demand of data storage. One of the main challenges in public cloud storage is to protect the security of data and to efficiently share data. In the past years, several papers in the literature have used proxy re-encryption (PRE) to address this challenge, where the performance of the underlying PRE scheme is very critical to the overall performance of the cloud storage. In this paper, we dedicate to design a secure and practical PRE scheme, which is CCA secure under the computational Diffie-Hellman (CDH) assumption in the random oracle model. We evaluate the efficiency of our scheme both in theoretical comparisons with related schemes and in implementations at several security levels using the recommended elliptic curve parameters from NIST, and the results indicate that our scheme can be practical in cloud-based data-sharing. © 2013 IEEE.Cloud storage allows users to access and store data in clouds over the internet, and provides a cheap and reliable solution for users with the demand of data storage. One of the main challenges in public cloud storage is to protect the security of data and to efficiently share data. In the past years, several papers in the literature have used proxy re-encryption (PRE) to address this challenge, where the performance of the underlying PRE scheme is very critical to the overall performance of the cloud storage. In this paper, we dedicate to design a secure and practical PRE scheme, which is CCA secure under the computational Diffie-Hellman (CDH) assumption in the random oracle model. We evaluate the efficiency of our scheme both in theoretical comparisons with related schemes and in implementations at several security levels using the recommended elliptic curve parameters from NIST, and the results indicate that our scheme can be practical in cloud-based data-sharing. © 2013 IEEE