Phishing attacks represent one of the most persistent cybersecurity threats globally, exploiting human psychology rather than technical vulnerabilities to compromise sensitive information. Despite significant advancements in AI-driven detection systems and multi-factor authentication, the human factor remains the weakest link in digital security. This research presents a comprehensive analysis of phishing threats and proposes a User-Centric Phishing Prevention (UCPP) Framework designed to enhance cybersecurity resilience through behavioral reinforcement, awareness training, and policy integration. The study employs a mixed-methods analytical approach, synthesizing secondary data from cybersecurity reports, academic literature, and policy documents to identify critical vulnerabilities in user behavior. Key findings reveal that approximately 70% of users fail to identify phishing indicators despite awareness of cyber threats, with social engineering tactics exploiting trust and urgency remaining the primary attack vectors. The proposed UCPP Framework integrates three core pillars: Awareness and Education, Technology Integration, and Policy Governance, achieving 92% alignment with national cybersecurity standards including CERT-In guidelines and the Digital Personal Data Protection Act (2023). Validation through expert review and triangulation confirms high practicality and scalability across diverse organizational and educational environments. The framework demonstrates significant potential for reducing phishing susceptibility through simulation-based training, adaptive AI-assisted detection, and standardized incident response protocols, contributing to the development of sustainable cybersecurity practices in developing digital ecosystems.
Building similarity graph...
Analyzing shared references across papers
Loading...
Vinay Sunil Gaykhe
D.Y. Patil University
Building similarity graph...
Analyzing shared references across papers
Loading...
Vinay Sunil Gaykhe (Sat,) studied this question.
www.synapsesocial.com/papers/69eb0bfa553a5433e34b5781 — DOI: https://doi.org/10.5281/zenodo.19413065