Graph-Based Android Malware Detection and Categorization through BERT Transformer

In this paper, we propose a novel approach to Android malware analysis and categorization that leverages the power of BERT (Bidi-rectional Encoder Representations from Transformers) to classify API call sequences generated from Android API Call Graph. By utilizing the API Call Graph, our approach captures the intricate re-lationships and dependencies between API calls, enabling a deeper understanding of the behavior exhibited by Android malware. Our results show that our approach achieves high accuracy in classi-fying API call sequences as malicious or benign and the method provides a promising solution also for categorizing Android mal-ware and can help mitigate the risks posed by malicious Android applications.