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Social engineering is a method of information security that allows for system or network access. When victims are unaware of techniques, models, and frameworks to prevent them, social engineering attacks happen. In order to stop social engineering attacks, the current research describes user studies, constructs, assessment, concepts, frameworks, models, and techniques. Sadly, there isn't any specific prior research on mitigating social engineering attacks that thoroughly and efficiently analyzes it. Health campaigns, human security sensor frameworks, user-centric frameworks, and user vulnerability models are examples of current social engineering attack prevention techniques, models, and frameworks. Guidance is required to examine cybersecurity as super-recognizers, possibly acting as police for a secure system, for the human as a security sensor architecture. This research aims to critically and systematically analyze earlier material on social engineering attack prevention strategies, models, and frameworks. Based on Bryman & Bell's methodology for conducting literature reviews, we carried out a systematic review of the available research. Using a protocol, we discovered a novel strategy to stop social engineering assaults in addition to approaches, frameworks, models, and assessments, based on our review. We discovered that the protocol can successfully stop social engineering assaults, including health campaigns, the susceptibility of social engineering victims, and co-utile protocol, which can control information sharing on a social network. This comprehensive evaluation of the research is what we're presenting in order to suggest safeguards against social engineering assaults.