User authentication is a measurement challenge for handheld devices and online accounts such as bank accounts, social media accounts etc. because illegal access results in money loss and user privacy. individual devices, online financial services, and intelligent spaces are three significant areas of concern for customer authentication procedures. Three ways have been identified for authentication factors: i) knowledge-factor, ii) inherence factor, and iii) possession-factor. This study investigates two-way user authentication through image processing. CNN, RCNN, and Deepface are deep learning algorithms used for image recognition. We used imagechain for image storage and Blockchain for personal information storage (mobile number) to secure the database. The database is stored on an Ethereum-based blockchain. After determining whether the image is fake or real, match the webcam image with the imagechain; if both images match, the one-time password is given to the user's cellphone number for login access. For image processing, Opencv is employed, and the Python library is used to execute machine and deep learning algorithms for user authentication. Test the proposed model on the 10 to 100 users for authentication. Accuracy of this experiment is 75.35, 76.33, 98.18 and cosine similarities of images are much better between images, but in case of fake image identification it achieved 97.35 % accuracy.

Origin of the coronavirus was the seafood market of Wuhan city, Hubei province in China. The cases of someone suffering from COVID-19 can be traced back to the end of December 2019 in China. This is the most infectious disease and spread worldwide within three months after the first case reported. The World Health Organization renames Coronavirus as COVID-19. COVID-19 is the β-Coronavirus family virus, effect on the lung of human and common symptoms are cough, fever, fatigue, respiratory problem, and cold. The full name of the coronavirus is severe acute respiratory syndrome SARS-CoV. It spread on humans as well as animals and infected more than 183 countries with 2959927 confirm cases and 202733 deaths till 28 April 2020. 84 days data is used to predict confirmed and death cases for the next 10 days by using prophet and daily average based algorithm. Predicted confirmed cases are 2886183 and death cases 190540 till 25 April 2020. This study introduces the spreading pattern of COVID-19 in the top ten infected countries. After China, European countries are the most infected ones. In this study, data was analyzed on the attributes confirmed, active, recovered and death cases, and next ten days outbreak prediction. Some countries state-wise data confirmed active and death cases also analyzed.