A framework for evaluating security, trust, and efficiency of sustainable Cloud Computing for Big Data processing

This thesis establishes a framework relying on the security of the BigCloud architecture to improve security issues. Specifically, this thesis research aims to examine the common features and the security challenges of this integration to provide an architecture relying on the security analysis, eva...

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Detalles Bibliográficos
Autor: Naser Ahmad Aladwan, Mohammad
Tipo de recurso: tesis doctoral
Fecha de publicación:2020
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/23605
Acceso en línea:http://hdl.handle.net/10347/23605
Access Level:acceso abierto
Palabra clave:Materias::Investigación::12 Matemáticas::1203 Ciencia de los ordenadores::120399 Big Data
Materias::Investigación::12 Matemáticas::1203 Ciencia de los ordenadores::120312 Bancos de datos
Materias::Investigación::12 Matemáticas::1203 Ciencia de los ordenadores::120317 Informática
Descripción
Sumario:This thesis establishes a framework relying on the security of the BigCloud architecture to improve security issues. Specifically, this thesis research aims to examine the common features and the security challenges of this integration to provide an architecture relying on the security analysis, evaluation theory, and security by design of the cloud deployment architecture to improve the large-scale data processing security issues. Also, it aims at enhancing the cloud-based BD frameworks security in storage, motion, and process. Implementing best guidelines and practices for managing security related to BD operations over cloud computing technology and updating industry security guidelines, frameworks, and standards are of this thesis concerns. Moreover, this thesis introduces an analytical model for data-intensive use case (i.e., Iot-to-cloud data streaming) security measurements, within any cloud-based framework. The thesis aims to fill the existing gap between the statistical representation of quality approaches of software engineering and the analysis of securing BD applications. Also, recommend best practices and measurements when constructing BD systems in both centralized and decentralized clouds. The proposed reference model and framework provides a comprehensive and fundamental basis to optimize the design of BigClouda frameworks regarding security ultimately.