Multi-Modal Biometric-based Threat Detection for Securing Electronic Voting Processes

The security and integrity of electronic voting systems are the two most important factors that can affect the effectiveness of the current democratic process. paper suggests a new way of making e-voting systems more secure through the implementation of real-time threats detection using biometric analysis and video surveillance. The system that is suggested uses the face recognition technique, the monitoring of body temperature, and the heart rate analysis, which are data collected through IoT devices, to identify the possible cases of voter intimidation or coercion during the voting process. Afterward, real-time video footage is captured and securely stored and so may help with a visual audit trail for post-election review. Also, the threat detection model, tested in controlled environments, showed a 95% success rate in the identification of stress and potential threats. These results point to the conclusion that the combined application of biometric and video technologies can have an amazing impact on the security and trustworthiness of e-voting systems, which will be able to defy the threats of manipulations and inducements much more effectively.