Enforcing Distributed Database Security using Multi-Scope based Authentication and Enhanced Distributed Firewall

2018 ◽  
Vol 6 (8) ◽  
pp. 1
Author(s):  
Surya Pratap Singh ◽  
Arvind Kumar Maurya ◽  
Manish Mishra ◽  
Upendra Nath Tripathi
Keyword(s):  
Relational Database ◽  
Network Architecture ◽  
Distributed Database ◽  
Database System ◽  
Database Security ◽  
Distributed Network ◽  
Prime Concern ◽  
Different Types ◽  
Distributed Firewall

The data is the most valuable asset of any organization, it resides data in the database system that is used to store data of every running application. So the security of database is very important. One of the most widely used types of a database is Distributed Database which has the capabilities of both a relational database and distributed network architecture. Hence the security of database is of the prime concern and at the same time, it is very tough to ensure, because different types of attackers and hackers are trying everything to compromise the distributed database security. Various researches are done to preserve the distributed database security but some security problems are still unresolved. In this paper, we propose the use of Multi-scope based authentication and Enhanced Distributed firewall by which the integrity and security of distributed database can be achieved.

scholarly journals Framework for Client-Server Distributed Database System for Federal Road Safety Commission Nigeria

2020 ◽  
Vol 7 (5) ◽  
pp. 440-451
Author(s):  
Sese Tuperekiye E.
Keyword(s):  
Local Government ◽  
Road Safety ◽  
Network Architecture ◽  
Distributed Database ◽  
Distributed Network ◽  
Client Server ◽  
Road Users ◽  
Access Information ◽  
Distributed Database System ◽  
Access Data

In recent years it has been observed that the federal road safety commission FRSC has been having some challenges on how to handle traffic rule and traffic offences committed by road users both commercial and private. Based on the in ability of the FRSC to handle these problems this paper critically looked into the behavioural pattern of the drivers towards traffic rules and offences committed and found that there was a great need for the Organisation to have a good database, that will be able to keep records of traffic offences and offenders, which can be called upon at any time on reference basis. The aim of this study is to create a distributed Federal Road Safety commission traffic offence system that can access data from any state of the Federation. The system consists of a relational database of FRSC variables which could be shared by the various States and Local Government Areas in the country. Each of the local government area will form a website, and the database will be hosted by the server at the Federal Road Safety Commission Head Quarters at Abuja and at the various state capital. . All LGAs will access the database via a distributed network. The client/server distributed network architecture is used in the design and implementation of the system. The system is capable of monitoring all road offences and traffic offenders records at all levelsfrom  any part of the country and generation of reports concerning offenders and also access information from the local government at all times.

Source-Oriented Data Processing. The triumph of the micro over the macro?

1996 ◽  
Vol 8 (3) ◽  
pp. 160-168 ◽  
Author(s):  
Janet Burt ◽  
Tom Beaumont James
Keyword(s):  
Data Processing ◽  
Relational Database ◽  
Database System ◽  
Relational Database System ◽  
Historical Databases ◽  
Oriented Approach

This article discusses the different approaches to the treatment of historical databases: the relational database system and κλειω, a source-oriented approach.

Performance Evaluation of Distributed Database Systems

2014 ◽  
Vol 13 (9) ◽  
pp. 4859-4867
Author(s):  
Khaled Saleh Maabreh
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Operation Mode ◽  
Database Systems ◽  
Distributed Database ◽  
Evaluation Study ◽  
Distributed Database Systems ◽  
Different Types ◽  
Distributed Database System ◽  
Distributed Database Management

Distributed database management systems manage a huge amount of data as well as large and increasingly growing number of users through different types of queries. Therefore, efficient methods for accessing these data volumes will be required to provide a high and an acceptable level of system performance.  Data in these systems are varying in terms of types from texts to images, audios and videos that must be available through an optimized level of replication. Distributed database systems have many parameters like data distribution degree, operation mode and the number of sites and replication. These parameters have played a major role in any performance evaluation study. This paper investigates the main parameters that may affect the system performance, which may help with configuring the distributed database system for enhancing the overall system performance.

scholarly journals Fighting Together against the Pandemic: Learning Multiple Models on Tomography Images for COVID-19 Diagnosis

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 261-273
Author(s):  
Mario Manzo ◽  
Simone Pellino
Keyword(s):  
Network Architecture ◽  
State Of The Art ◽  
Ensemble Classification ◽  
Effective Vaccine ◽  
Rt Pcr ◽  
Neural Network Architecture ◽  
Experimental Phase ◽  
Different Types ◽  
Polymerase Chain ◽  
Better Than

COVID-19 has been a great challenge for humanity since the year 2020. The whole world has made a huge effort to find an effective vaccine in order to save those not yet infected. The alternative solution is early diagnosis, carried out through real-time polymerase chain reaction (RT-PCR) tests or thorax Computer Tomography (CT) scan images. Deep learning algorithms, specifically convolutional neural networks, represent a methodology for image analysis. They optimize the classification design task, which is essential for an automatic approach with different types of images, including medical. In this paper, we adopt a pretrained deep convolutional neural network architecture in order to diagnose COVID-19 disease from CT images. Our idea is inspired by what the whole of humanity is achieving, as the set of multiple contributions is better than any single one for the fight against the pandemic. First, we adapt, and subsequently retrain for our assumption, some neural architectures that have been adopted in other application domains. Secondly, we combine the knowledge extracted from images by the neural architectures in an ensemble classification context. Our experimental phase is performed on a CT image dataset, and the results obtained show the effectiveness of the proposed approach with respect to the state-of-the-art competitors.

Scalable linear algebra on a relational database system

2020 ◽  
Vol 63 (8) ◽  
pp. 93-101
Author(s):  
Shangyu Luo ◽  
Zekai J. Gao ◽  
Michael Gubanov ◽  
Luis L. Perez ◽  
Dimitrije Jankov ◽  
...  
Keyword(s):  
Linear Algebra ◽  
Relational Database ◽  
Database System ◽  
Relational Database System
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