Controlling Software and Hardware Theft in college Laboratory through Image Processing

Information Technology

Theft is being always a biggest threat to the security of the premises which leaves the owner of the premises completely shuttered. This theft is even a curse at the educational organizations where theft of any equipment or any hardware peripherals always creates a havoc to the other students. This theft includes the theft of software and hardware by the known or unknown persons who access the facility on the premises. So to deal with this kind of scenario proposed methodology put forward an idea of providing a security for the data and also to the devices. Proposed model allows the admin of the system to register the students with their images. So as the registered or unregistered student access the computer on the premises then based on the permission given to them, the system will shut down to prevent any data theft. On hardware theft like mouse and keyboard proposed model will raise an alert to inform the admin. This model is deployed using the face detection and recognition using the Deep convolution neural network.

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