Enhancing AppAuthentix recommender systems using advanced machine learning techniques to identify genuine and counterfeit android applications.

ABSTRACT: Smartphone app expansion needs strict security measures to avoid fraud and danger. This study overcomes this issue by identifying apps differently. This new solution uses convolutional neural network (CNN), natural language processing (NLP), and the strong AppAuthentix Recommender algorithm to secure app stores and boost customer confidence in the digital marketplace. Since the app ecosystem has grown, counterfeit and harmful applications have risen, threatening consumers and app merchants. These risks need advanced technology that can distinguish malware from legitimate apps. A complex prediction model using CNNs for image analysis, NLP for text feature extraction, and the novel AppAuthentix Recommender algorithm to properly identify legitimate and counterfeit mobile applications is the g

SUBMITTER: M R 

PROVIDER: S-EPMC11622937 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature