Assessing data phishing risks associated with unencrypted apps on smartphones with non-parametric test and random forest model: Insights from Kuwait phishing scam calls

The outbreak of covid-19 has helped M-commerce to strengthen its roots and helped to increase the number of customers in different industries. Likewise, Electronics product companies also developed M-commerce platforms such as mobile applications (Apps) regardless of their website to sell their products based on customers’ interests and likes. In order to create personalized and targeted marketing strategies, companies collect data from users of M-commerce platforms. For this, they have taken the data from the Handheld device users who installed the companies’ applications with or without the consent of the users which raises ethical concerns related to privacy and security. Unlike other studies this research explores the reason of increased data phishing cases in Kuwait from 2020 and the findings are supported by statistics using machine learning and python language. This paper examines the ethical implications-data phishing chances from users if M-commerce platforms of electronics Apps which are data unencrypted installed in the smartphones. The study employs a mixed-methods approach that includes semi-structured interviews with industry experts and customers, Checking the M-commerce Data privacy details, and analysis of relevant literature. Using the study's survey findings, the hypothesis was tested and a machine learning model was developed that predicts the likelihood of data theft when two specific apps are installed on a smartphone. The research pointed out that the null hypothesis is true and there is approximately 82% of chance if the smart phone users installs data unencrypted apps in the device.