Baiting Attack Simulation and Prevention System in Cyber Security

Abstract

Cybersecurity threats are increasing rapidly due to the growth of internet communication, social engineering attacks, and malicious digital content. Among various cyber threats, baiting attacks are one of the most dangerous forms of social engineering attacks in which attackers attract users through fake software downloads, gift vouchers, infected USB devices, and malicious advertisements to gain unauthorized access to sensitive information. Many users unknowingly interact with suspicious files and external devices due to lack of cybersecurity awareness. This paper presents a Baiting Attack Simulation and Prevention System in Cyber Security that focuses on simulating baiting attack scenarios, detecting suspicious files and USB devices, monitoring user interactions, and generating real-time alerts to improve cybersecurity awareness. The proposed framework integrates USB monitoring, suspicious download detection, bait file simulation, logging mechanisms, and user awareness modules into a unified cybersecurity platform. The system continuously analyzes suspicious activities and maintains threat logs for security analysis. Experimental analysis demonstrates that the proposed framework improves threat detection accuracy, enhances user awareness, and reduces the risk of malware infection and unauthorized system access.