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Application of Rules and Authorization Key for Secured Online Training—A Survey
International Conference on Sustainable Expert Systems, ICSES 2020 ; 176 LNNS:41-51, 2021.
Article in English | Scopus | ID: covidwho-1265475
ABSTRACT
Online training has been present for over a decade, and its importance is increasing every day. Today, it has become very important due to ongoing COVID-19 pandemic. As it has been accepted widely by the educational systems;nowadays, challenges like hardware resources, network resources, software resource, and security have become more demanding. Security threats among all challenges require more researches to develop rigid systems where data of all stakeholders remain secured. ML has a proven track record to solve such problems. In terms of security, ML continuously learns by analyzing data to find patterns so unauthorized access to encrypted traffic is detected better and find insider threats to keep information safe. Here, a new system is being developed using an improved algorithm, described in proposed work. Using this new algorithm, machines are trained to identify unauthorized access attempts and stop them from stealing data even if, they are authenticated. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Observational study Language: English Journal: International Conference on Sustainable Expert Systems, ICSES 2020 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Observational study Language: English Journal: International Conference on Sustainable Expert Systems, ICSES 2020 Year: 2021 Document Type: Article