The COVID-19 pandemic is causing a worldwide emergency in healthcare. This virus mainly spreads through droplets which emerge from a person infected with coronavirus and poses a risk to others. The risk of transmission is highest in public places. One of the best ways to stay safe from getting infected is wearing a face mask in open territories as indicated by the World Health Organization (WHO). In this project, we propose a method which employs TensorFlow and OpenCV to detect face masks on people. A bounding box drawn over the face of the person describes weather the person is wearing a mask or not. If a person s face is stored in the database, it detects the name of the person who is not wearing face mask and an email will be sent to that person warning them that they are not wearing a mask so that they can take precautions.

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In this paper, we present a comprehensive picture and the state of the art of Identity Based Cryptography (IBC) and their security implications with applications. First, we introduce the basic concepts of security and principles of cryptography and then move into identity-based cryptography, an overview of its development process and research progress. We explain identity-based encryption (IBE) schemes and identity-based signature (IBS) schemes and their security analysis. Later, we discuss the hierarchical identity-based encryption (HIBE) present in standard model as well as in random oracle model. We also discuss Revocable Identity Based Encryption (RIBE) schemes from the view point of security models and constructions.We review several encryption schemes and their advantages and disadvantages along with their efficiency and security considerations General TermsCryptography, Security.

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