Provenance-Aware NoSQL Databases

2016 ◽  
pp. 152-160 ◽  
Author(s):  
Anu Mary Chacko ◽  
Munavar Fairooz ◽  
S. D. Madhu Kumar
Keyword(s):  
Nosql Databases

An Efficient, Secure, and Queryable Encryption for NoSQL-Based Databases Hosted on Untrusted Cloud Environments

2019 ◽  
Vol 13 (2) ◽  
pp. 14-31
Author(s):  
Mamdouh Alenezi ◽  
Muhammad Usama ◽  
Khaled Almustafa ◽  
Waheed Iqbal ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Query Processing ◽  
State Of The Art ◽  
Data Communication ◽  
Nosql Databases ◽  
High Concern ◽  
Cloud Environments ◽  
High Scalability ◽  
And Performance ◽  
Secure Query Processing ◽  
Security Concern

NoSQL-based databases are attractive to store and manage big data mainly due to high scalability and data modeling flexibility. However, security in NoSQL-based databases is weak which raises concerns for users. Specifically, security of data at rest is a high concern for the users deployed their NoSQL-based solutions on the cloud because unauthorized access to the servers will expose the data easily. There have been some efforts to enable encryption for data at rest for NoSQL databases. However, existing solutions do not support secure query processing, and data communication over the Internet and performance of the proposed solutions are also not good. In this article, the authors address NoSQL data at rest security concern by introducing a system which is capable to dynamically encrypt/decrypt data, support secure query processing, and seamlessly integrate with any NoSQL- based database. The proposed solution is based on a combination of chaotic encryption and Order Preserving Encryption (OPE). The experimental evaluation showed excellent results when integrated the solution with MongoDB and compared with the state-of-the-art existing work.

scholarly journals Benchmarking Big Data OLAP NoSQL Databases

2018 ◽  
pp. 82-94 ◽  
Author(s):  
Mohammed El Malki ◽  
Arlind Kopliku ◽  
Essaid Sabir ◽  
Olivier Teste
Keyword(s):  
Big Data ◽  
Nosql Databases

Formalizing the Mapping of UML Conceptual Schemas to Column-Oriented Databases

2018 ◽  
Vol 14 (3) ◽  
pp. 44-68 ◽  
Author(s):  
Fatma Abdelhedi ◽  
Amal Ait Brahim ◽  
Gilles Zurfluh
Keyword(s):  
Big Data ◽  
Data Warehouse ◽  
Relational Databases ◽  
Traditional Approach ◽  
Physical Models ◽  
Decision Making Process ◽  
Nosql Databases ◽  
Care Field ◽  
Sufficient Degree

Nowadays, most organizations need to improve their decision-making process using Big Data. To achieve this, they have to store Big Data, perform an analysis, and transform the results into useful and valuable information. To perform this, it's necessary to deal with new challenges in designing and creating data warehouse. Traditionally, creating a data warehouse followed well-governed process based on relational databases. The influence of Big Data challenged this traditional approach primarily due to the changing nature of data. As a result, using NoSQL databases has become a necessity to handle Big Data challenges. In this article, the authors show how to create a data warehouse on NoSQL systems. They propose the Object2NoSQL process that generates column-oriented physical models starting from a UML conceptual model. To ensure efficient automatic transformation, they propose a logical model that exhibits a sufficient degree of independence so as to enable its mapping to one or more column-oriented platforms. The authors provide experiments of their approach using a case study in the health care field.

Reverse Engineering Approach for NoSQL Databases

2020 ◽  
pp. 60-69
Author(s):  
Fatma Abdelhedi ◽  
Amal Ait Brahim ◽  
Rabah Tighilt Ferhat ◽  
Gilles Zurfluh
Keyword(s):  
Reverse Engineering ◽  
Nosql Databases ◽  
Engineering Approach
Sign in / Sign up

Export Citation Format

Share Document