Anti-tailgating solution using biometric authentication, motion sensors and image recognition

Tailgating is a social engineering attack challenging physical security within organizations. It gained public traction in the year 1999 and has since remained a major concern in the field of security leading to the development of several anti-tailgating solutions. These solutions began with simple mechanisms like mechanical turnstiles, revolving doors, and man-trap systems and evolved into more modern technologies using infrared beams, 3D machine vision, face detection, BMI and face recognition combination, and an embedded solution using IP camera and video analytics. A critical analysis of these solutions uncovered certain weaknesses which run through most of them. These are the inability to detect two people side by side and the incapability of detecting multiple entries after a single access authorization. These shortfalls led to the development of the solution in this paper which aims to eliminate the shortcomings of existing technologies and boost security, by using a three-step anti-tailgating solution. The design science research methodology and aspects of qualitative and quantitative research are employed in designing a three-step anti-tailgating solution that combines face detection, palm recognition, and motion sensors, to eliminate the loopholes of existing technologies. The results from experimentation indicated that the face detection tool could detect two faces present. The motion sensors were shown to be efficient in performing people counting and detection, to eliminate tailgating and discrepancies in the number of entries against the number of authorized personnel. Integrated with palm recognition the overall system will function effectively because the three technologies complement each other's shortfalls, therefore preventing tailgating. It is concluded that this system will be an improved and more effective anti-tailgating solution.