CYBER SECURITY FRAMEWORK FOR NIGERIAN CIVIL AVIATION AUTHORITY, HEADQUARTERS

Abstract

The practice of defending assets from unauthorized access, use, disclosure, disruption, modification, perusal, inspection, recording or destruction is as ancient as man’s existence on earth. Cybersecurity, information security, and computer security are
further attempts of man to continue the same ancient practice. This is due to the unavoidably prevalent need and use of information and communication technologies in this century, which has left the man with such vulnerability and insecurity
through its devices and infrastructures. The aviation industry, being one of the most economic and leisure viable industry in the
world has been at the top-notch of the use of these technologies for better services to man. Nigeria Aviation industry is one of the
largest and most viable in Africa is opened to the vulnerabilities and cyber threats that comes with these advanced technologies.
However, several methods and programs have been employed by various organizations and stakeholders, but, the Nigerian Civil
Aviation Authority (NCAA), been the apex governing body that control, monitor and regulate the economic and safety oversight of
the entire Aviation industry in Nigeria seems not to have gotten it right with the recent trends of cyber warfare in the industry as
opposed to their counterparts in the world over. Therefore, this research study attempts to employ data from existing literature
and questionnaires to analyze the existing practices of cyber/information security programs (if any) within the NCAA and to
design an adaptable cybersecurity framework that is robust enough for its safety. By using version 3.9.3 of Waikato Environment
for Knowledge Analysis (WEKA) software, Naïve Bayes, Bayes Net, Decision Table, IBK (Linear NNSearch), REP Tree, J48, SMO, Simple Logistic, and Bagging are the nine algorithms employed to determine and predict tier classes as existing profile and target profile respectively for NCAA within the framework. SMO emerge best fit to predict the target profile while the Bagging algorithm emerges best fit to determine the current profile. Gaps and implementable action plans were deduced. Thereafter, the RNA Cyber Security Framework (RNA-CSF) is conceptually developed, analyzed and proposed for NCAA and for any other organization that has the need to use it.