Issue |
ITM Web Conf.
Volume 56, 2023
First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|
|
---|---|---|
Article Number | 01003 | |
Number of page(s) | 6 | |
Section | Computational Intelligence and Computing | |
DOI | https://doi.org/10.1051/itmconf/20235601003 | |
Published online | 09 August 2023 |
A Novel Approach for clone app detection using VADER’s Algorithm
Department of Engineering, Sciences, and Humanities (DESH) Vishwakarma Institute of Technology, Pune, 411037, Maharashtra, India
sonali.antad@vit.edu
ayush.khambayate22@vit.edu
shreyas.khamkar22@vit.edu
om.khandare22@vit.edu
atharav.khaire22@vit.edu
prasad.khambadkar22@vit.edu
deep.khanchandani22@vit.edu
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.
Key words: Sentiment analysis / Positive – Negative Ratings / App Security / Machine learning Models / Behavioral Feature Extraction
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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