Cybersecurity Awareness Level: An Analytical Assessment of Knowledge, Practices, and Attitudes

P Sumalatha; D Sunil Kumar; M Santhosh; B Vandana; D Harshavardhan

doi:10.5281/zenodo.18596159

Authors

P Sumalatha Department of CSE (IoT, Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
D Sunil Kumar Department of CSE (IoT, Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
M Santhosh Department of CSE (IoT, Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
B Vandana Department of CSE (IoT, Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.
D Harshavardhan Department of CSE (IoT, Cyber Security including Block Chain Technology), Annamacharya Institute of Technology & Sciences (Autonomous), Tirupati, A.P, India.

DOI:

https://doi.org/10.5281/zenodo.18596159

Keywords:

Cybersecurity Awareness, Human-Centered Security, Cybercrime, Statistical Analysis, Survey-Based Assessment, Awareness Modeling

Abstract

Human factors are a significant factor in the security threat landscape, especially in the increasing trend of adopting digital technologies. This paper discusses a data-driven evaluation of security awareness, knowledge, practices, and response capacity of individuals in the central part of India. Our approach relies on a set of 284 valid responses from a survey that assessed four aspects: background knowledge, awareness of cybercrime, education level, and ability to cope with cybercrime. Reliability tests show that the instrument has acceptable internal consistency reliability, with a Cronbach’s alpha value of 0.67. Our regression analysis shows that awareness of cybercrime has the highest impact on the ability to cope with cybercrime, followed by background knowledge and education level, all of which are statistically significant at p < 0.05. In addition, this paper also discusses a web-based Cyber Security Awareness Level Assessment System, which facilitates the automation of data collection, evaluation, and analysis in assessing the level of security awareness among individuals in a particular institution and geographical location. Our proposed system helps transform subjective security awareness into objective security metrics, which are crucial in developing an effective security training plan and security policy. Results emphasize that cognitive awareness and educational exposure are statistically dominant predictors of cyber readiness, supporting the development of adaptive training models and evidence-driven cybersecurity policies. The architecture is scalable, modular, and suitable for institutional deployment, longitudinal studies, and regional cyber risk profiling.

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