A Novel Approach for clone app detection using VADER’s Algorithm

Abstract

Software that imitates the capabilities of legitimate, legally responsible, and authentic applications is known as a fraudulent web application. It’s critical to keep track of which mobile applications are secure and which aren’t as the number of them in our daily lives increases. One cannot judge the truth, and the only basis for judging each application is the opposing viewpoints that are stated for each application. Once the false program has been installed, the perpetrators carry out retaliatory acts such as aggressive ad display to recoup revenue, intercepting sensitive data from your system, polluting the impact device, and so forth. Users frequently cannot tell the difference between legitimate and fraudulent applications By developing a place where people can ask questions before installing the program, It is suggested to employ sentiment analysis (VADERS), which is a revolutionary method for detecting fraudulent apps.. The outcome is determined by the ratings and comments provided by users who have already used the application. As a result, we will use sentiment analysis to examine the viewpoints once more. Sentiment analysis will be carried out using the VADERS approach, which analyses text.

Keywords

• sentiment analysis
• positive – negative ratings
• app security
• machine learning models
• behavioral feature extraction