Authors:
Avinash Reddy Pothu
Addresses:
Department of Research and Development, Ginger Labs, Frisco, Texas, United States of America.
Abstract:
The swift nature of cybersecurity threats necessitates a thorough understanding of user behaviour in defending against threats. In this research, the behaviour of end-users while online and its implications for cybersecurity threats are considered. Based on common users' behaviours, risk disposition, and protective measures, the research identifies the causes of security failures. The research is a population survey conducted across diverse demographic populations to determine their awareness levels of security protocols. Measures utilised in the analysis are 500 responses from diverse demographics, phishing attack simulation metrics, and observational metrics of password management. The measures were sourced from open-source cybersecurity data sets and anonymised user data obtained during the research conducted. Packages such as Python (statistical analysis and data visualisation). This report contains the tools (Python, Graphviz, Microsoft Excel) for creating diagrams, designing data, and tabulating to represent and analyse results. The research suggests that less security-conscious users are more susceptible to phishing attacks and social engineering scams. The suggested framework consists of robust security controls and tailored training interventions to address such threats. A holistic behaviour-focused approach is encouraged to maximise threat prevention and security awareness practice. The results are applicable in the development of dynamic security solutions that react to user behaviour patterns for organisational and individual cybersecurity enhancement practices.
Keywords: Cybersecurity and User Behaviour; Threat Prevention; Social Engineering; Designing Data; Engineering Attacks; Training Interventions; Diverse Demographics.
Received: 08/05/2024, Revised: 22/06/2024, Accepted: 09/08/2024, Published: 01/03/2025
DOI: 10.64091/ATICL.2025.000094
AVE Trends in Intelligent Computer Letters, 2025 Vol. 1 No. 1 , Pages: 31-40