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Reseach Article

Missing Values Prediction for Cyber Vulnerability Analysis in Academic Institutions

by Bhavya Agrawal, Anurag Jain
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 43
Year of Publication: 2018
Authors: Bhavya Agrawal, Anurag Jain
10.5120/ijca2018917129

Bhavya Agrawal, Anurag Jain . Missing Values Prediction for Cyber Vulnerability Analysis in Academic Institutions. International Journal of Computer Applications. 180, 43 ( May 2018), 16-25. DOI=10.5120/ijca2018917129

@article{ 10.5120/ijca2018917129,
author = { Bhavya Agrawal, Anurag Jain },
title = { Missing Values Prediction for Cyber Vulnerability Analysis in Academic Institutions },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 180 },
number = { 43 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 16-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number43/29419-2018917129/ },
doi = { 10.5120/ijca2018917129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:03:29.570299+05:30
%A Bhavya Agrawal
%A Anurag Jain
%T Missing Values Prediction for Cyber Vulnerability Analysis in Academic Institutions
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 43
%P 16-25
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a survey-based study has been done to analyze the cyber security vulnerability of higher education institutions to identify the areas that are more prone to cyber threats at different user levels (System Administrator and Students & Faculty). One of the major elements of data mining- prediction of Missing Values has been amalgamated with vulnerability analysis of academic institutes to improve their practices and compliance of information security. These predictions help in identifying associations and handling missing data due to lack of awareness among users for more effective vulnerability analysis of the cyber security in academic environments. Subsequently, it will lead to formation of essential security guidelines that institutes can adopt to avoid above mentioned risks. Two theories have been proposed to identify the cyber vulnerabilities based on Questionnaire filled by different user levels. Prediction of missing values has also been evaluated after pre-processing and tried to filled the blank entities in the Questionnaire. The result shows that, after the prediction of missing values there is still significant number of students and faculty who are confused about the HR Policies of their institutes making their information security vulnerable. Hence guidelines to mitigate vulnerability issues have been proposed in this research work.

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Index Terms

Computer Science
Information Sciences

Keywords

Cyber security Vulnerability Analysis Information Security Security Guidelines Academic Institutes Naïve Bayes algorithm Prediction