Cyber Security Awareness (CSA) and Cyber Crime in Bangladesh: A Statistical Modeling Approach

Abstract

The need to combat cybercrime is becoming more and more urgent. This effect is crucial for developing nations like Bangladesh, which is currently building out its infrastructure in preparation for fully secure digitization. This study aims to identify the numerous factors that contribute to cybercrime, its challenges, the relationships between different cybersecurity variables, potential solutions to these issues, and various behavioral viewpoints individuals and organizations hold regarding cybercrime victimization. A simple random sampling method has been conducted to collect 200 data from individuals on this topic. Factor analysis based on Principal Component Analysis (PCA) was fitted to the data to analyze cyber behavior, Binary Logistic Regression was fitted to analyze cyber victimization status and the Poisson Regression model was fitted to analyze victimization frequency. The research demonstrates that the dependent variable cybercrime victimization is strongly associated with the independent variables which are password sharing status, using a common password, cyber security knowledge Status, personal information online storage status, downloading free antivirus from an unknown source, disabling antivirus for downloading, download digital media from an unknown source, clicking links unauthorized sites, personal info Sharing with a stranger over online. According to the regression model's findings, women are more likely than men to experience cybercrime. Cybersecurity knowledge is found to be a key factor in preventing cyberattacks. Additional research on this subject can be conducted utilizing large-scale data to gain more trustworthy conclusions on the underlying factors contributing to cybercrime victimization. Overall, developing a digital Bangladesh where our cyber security is robust can be accomplished by learning about cybersecurity and practicing safe online behavior.