COVID-19 global pandemic pushed a large number of higher educational institutions to use Online Proctored Exams (OPE) because of government-imposed lockdowns. Treating OPE as an educational technology innovation, we apply the diffusion of innovation theory in predicting factors affecting its adoption by university students which we believe is the first of its kind research study. The study presented here reviews OPE, its types, architecture, challenges, and prospects and then focuses on the student adoption experience at a large, multi-campus higher educational institution. We have used the fine-grained Aspect Level Sentiment Analysis to check the university students’ attitudes towards the Online Proctored Exams. We then used linguistic features to extract the aspect terms present in the feedback comments which showed that 55% of university students having a positive attitude towards OPE. Results of our study show that innovation characteristics such as relative advantage, compatibility, ease of use, trialability, and observability were found to be positively related to acceptance of OPE.

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Encryption methods such as AES (Advanced Encryption Standard), DES (Data Encryption Standard), etc. cannot be used for image encryption as images contain a huge amount of redundant data, a high correlation between neighboring pixels and size of the image is very large. Chaosbased techniques have suitable properties that are required for image encryption. The properties include sensitivity to initial conditions, pseudorandom number, ergodicity, and density of periodic orbits. In this paper, a survey of image encryption using chaos-maps such as a logistic map, piecewise linear chaotic map (PWLCM), tent map, etc. is done in order to choose best map for image encryption. Comparison of image encryption using different chaotic maps is done by considering parameters such as key-space and correlation analysis.