Social Engineering Techniques in Cybersecurity and Corresponding Mitigating Strategies

Social engineering is a growing cybersecurity threat that exploits human vulnerabilities rather than technical weaknesses. This study investigates the effectiveness of various social engineering techniques, and potential countermeasures to mitigate these threats. The primary objective of this research is to analyze the role of social engineering in cybersecurity by testing different attack methods and evaluating their success rates. The study employs a simulation-based approach in a controlled environment using tools such as the Social Engineer Toolkit (SET), Metasploit Framework, and wireless network attack tools. Four attack scenarios were conducted: phishing, Remote Access Trojan (RAT), web jacking, and the Problem-Agitation-Solution (PAS) attack. Data was collected based on the success rates of these attacks. Key findings from the simulations indicate that social engineering techniques are highly effective, with the PAS attack showing the highest success rate. The study highlights the psychological manipulation tactics used by attackers to exploit trust, urgency, and fear. The research also underscores the risks posed by phishing attacks and web jacking, which trick users into revealing sensitive information. The study recommends several mitigation strategies, including user education and awareness training, robust security measures such as firewalls and intrusion detection systems, regular security audits, and the implementation of strong password policies. The results emphasize the need for organizations to prioritize cybersecurity awareness programs to reduce susceptibility to social engineering attacks. While technical security solutions are essential, human factors remain the weakest link in cybersecurity. Future research should expand the sample size, explore additional attack scenarios, and assess the effectiveness of advanced mitigation strategies in real-world environments.