Reducing Threats by Using Bayesian Networks to Prioritize and Combine Defense in Depth Security Measures
This paper analysed whether the Bayesian Network Model (BNM) can be effectively used to prioritise in-depth security tools and procedures for protection and to combine those steps to reduce cyber threats. A balance between the defence capability and cost , efficiency, and operational considerations is recommended by the strategy. The methods used in this study were to search 24 peer-reviewed cybersecurity papers from leading cybersecurity journals using the Likert Scale Model for the article’s list of in-depth safety measures (tools and procedures) and the risks to be mitigated by those measures. In order to see if the Likert scale and the Bayesian Network Model could be effectively implemented to prioritise and combine steps to minimise cyber attacks against organisational and private computing networks, the security tools and procedures were then compared. The study results refute the H0 null hypothesis that the relationship between the prioritisation and the combination of 24 Cybersecurity Article safety instruments and procedures (independent variables) and cyber threats (dependent variables) is not influenced by BNM.
Dr. Rodney Alexander
Hutchinson Community College, Hutchinson, Kansas, USA.
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