مجلة الاربعين المحكمة
Objective: This research study focuses on understanding cybersecurity threats of Internet of Things (IoT) devices with special attention towards cyber attacks that relate to mega events such as Arbaeen Pilgrimage. With an objective to guard the users and their equipment in a mega event scenario, this project would identify weaknesses of the IoT system, develop means for cyber threat detection and also give recommendations for risk neutralization in an efficient manner. Methodology: A mixed-method strategy combining qualitative and quantitative research methods is employed in this research. A thorough review of the existing body of research on IoT security issues and attack techniques is conducted. In addition to this, primary data from surveys and expert interviews conducted with cybersecurity professionals are utilized. In order to analyze actual vulnerabilities in IoT systems, a case study on the Arbaeen Pilgrimage is studied. Cyber threat detection models are created by applying machine learning methods, and simulation tools are used to check how well the mitigation techniques work. Key Findings: IoT devices are particularly vulnerable to all types of cyberattacks, including DDoS, unauthorized access, and data breaches, particularly during peak events like the Arbaeen Pilgrimage. Existing IoT security measures often fail to detect and prevent these threats in real- time, putting both users and devices at risk. Nevertheless, the study of suspicious activity patterns and anomalies can serve as a strong base in which machine learning algorithms might be useful for the identification and mitigation of cyber threats. Strong security features, including intrusion detection systems, regular firmware upgrades, and multi-factor authentication, must be incorporated into IoT devices for general security