TOWARDS A SECURED DESIGN METHODOLOGY FOR CLOUD BASED BIOINFORMATICS APPLICATIONS

A. Nasir, M. U. G. Khan

A. Nasir and M. U. G. Khan

Department of Computer Science and Engineering, Bio-informatics Lab, Al-Khwarizmi Institute of computer Sciences
University of Engineering and Technology, Lahore, Pakistan

Corresponding Author: nasir_bhutta@yahoo.com
Page Number(s): 1176-1182
Published Online First: August 01, 2015
Publication Date: August 01, 2015

ABSTRACT

The amount of molecular biology data currently being generated from the lab based testing and conventional computing techniques was not thought before. But at the same time the existing techniques remains incapable to cater this massive amount data sets to retrieve meaningful results in an efficient manner. With the exponential growth of computing applications and their corresponding users, many evolutionary systems have appeared in the current markets, such as cloud computing, grid computing, bioinformatics, and video surveillance systems. Though the discovery of such systems has brought fruitful changes in daily lives of their users, there are several severe problems associated with such computing environments and security is one of the most critical issues faced by the users and service providers of these applications. These security issues and problems may arise during the life span of any evolutionary domain i.e. they are dynamic in nature as they arise and need to be handled during their life span. In this paper, we have introduced a secured methodology for designing evolutionary computing applications. We further present a working system from bioinformatics domain for testing and evaluation of the proposed design methodology.

Keywords: Cloud Computing, Bioinformatics, Evolutionary System, Secured Design Methodology, Software Engineering, Software Designs
Open Access: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).


Download Statistics
This Manuscript
Full Text
22
downloads
Indicators
Metrics

Cite Score: 1.3

JCR Year: 2025

Indexing
Status

Web of Science (SCIE)

SCOPUS (Q3)

Journal Metrics
Current

Journal Impact Factor: 0.5

HEC Category: W

ISSN Details
Verified

Print ISSN: 1018-7081

Electronic ISSN: 2309-8694

Search the Journal

Use the fields below to search for articles by Title, Author, or Keywords.

All Downloads
Full Text
85,080
downloads
Supplementary
263
downloads