A User Oriented, Flexible Real-Time Motion Triggered Surveillance System for Highly Restricted Areas

Abstract

Phishing remains a significant social engineering tool exploited by hackers, especially with the increasing adoption of internet technology leading to a surge in attacks. This systematic literature review explores techniques aimed at detecting and preventing spear phishing attacks. Analyzing 106 papers using the PRISMA framework revealed a high accuracy range of 88% to 99.4% achieved by researchers. However, it was noted that datasets for spear phishing detection are limited, and there's an underutilization of hybrid machine learning approaches. Therefore, future research should focus on exploring and combining various machine learning algorithms to enhance detection and prevention capabilities.