A two-tier database architecture framework for combating cyber threats

The 21st century has witnessed a lot of advancements in science and technology. One may not be wrong to assert that the field of Information and Communications Technology (ICT) and its allied disciplines like Artificial Intelligence (AI) and Nanotechnology have taken the lead as we witness new developments in these areas year by year. The products and services we utilize and enjoy are evidence of the usefulness of this advancement in science and technology. It is worthy of note that the interest of many (both good and bad in the discipline of ICT), is being ignited by the fact that ICT finds its applicability virtually in every area of human endeavor. In this study, we propose a two tier database architecture that employs an Object-Oriented Analysis Design Methodology (OOADM) using the Unified Modelling Language (UML). The choice of this methodology is because we need to present every stage of the study from analysis to the design phases. With the help of the chosen methodology, we analyzed the existing frameworks, identified the weaknesses, and as a result, we further surveyed algorithms used for reliable data security. From the results obtained from the survey, we employed the SHA-256 algorithm because of its strength in data security, and the Argon2 hashing algorithm which is one of the best algorithms for securing database credentials. In the end, we provide an enhanced framework made up of the chosen algorithms and a two-dimensional database (2-DDb), which could be implemented to effectively combat attacks on important databases.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-30
DOI
https://doi.org/10.5281/zenodo.15039370
Primary Topic
Ultrasound in Clinical Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A two-tier database architecture framework for combating cyber threats

Zenodo (CERN European Organization for Nuclear Research)
Ultrasound in Clinical Applications
article

A two-tier database architecture framework for combating cyber threats

article en

Abstract

The 21st century has witnessed a lot of advancements in science and technology. One may not be wrong to assert that the field of Information and Communications Technology (ICT) and its allied disciplines like Artificial Intelligence (AI) and Nanotechnology have taken the lead as we witness new developments in these areas year by year. The products and services we utilize and enjoy are evidence of the usefulness of this advancement in science and technology. It is worthy of note that the interest of many (both good and bad in the discipline of ICT), is being ignited by the fact that ICT finds its applicability virtually in every area of human endeavor. In this study, we propose a two tier database architecture that employs an Object-Oriented Analysis Design Methodology (OOADM) using the Unified Modelling Language (UML). The choice of this methodology is because we need to present every stage of the study from analysis to the design phases. With the help of the chosen methodology, we analyzed the existing frameworks, identified the weaknesses, and as a result, we further surveyed algorithms used for reliable data security. From the results obtained from the survey, we employed the SHA-256 algorithm because of its strength in data security, and the Argon2 hashing algorithm which is one of the best algorithms for securing database credentials. In the end, we provide an enhanced framework made up of the chosen algorithms and a two-dimensional database (2-DDb), which could be implemented to effectively combat attacks on important databases.

Zenodo (CERN European Organization for Nuclear Research)
Ambrose Alli University (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 55%
Ultrasound in Clinical Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.