Criticality of E-Privacy and Data Leakage Amid the Pandemic: Privacy-Preserving Techniques and Frameworks

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Author(s): Gaurav Roy (EC Council University, India)
Copyright: 2021
Pages: 7
Source title: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Source Author(s)/Editor(s): Manikant Roy (Lovely Professional University, India)and Lovi Raj Gupta (Lovely Professional University, India)
DOI: 10.4018/978-1-7998-7188-0.ch013

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Information Science Reference / Medical Technologies

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Abstract

The global pandemic has led to an undeniable surge in using digital technologies due to the social distancing norms and nationwide lockdowns. Firms and organizations are conforming to the new culture of work and life. The use of internet services, digital devices, and cloud systems has seen surges in usage from 40% to 100%, compared to pre-lockdown levels. With the rapid growth of this technological use, people are exposing their digital assets, presence, and behavior out to the binary world where AI-driven data analysis algorithms, data-gathering systems, and spyware are continuously monitoring their behavior. These subconsciously exposed data are then carried forward for delivering customized ads and recommend features.

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Criticality of E-Privacy and Data Leakage Amid the Pandemic: Privacy-Preserving Techniques and Frameworks

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