J. Antony

Android Malware Detection Using a Hybrid XGBoost–Random Forest Model with Cost-Sensitive Learning

Android apps have more users and consequently are more susceptible to smart malware, raising significant privacy, data protection, and security concerns. While machine-learning approaches to malware detection have yielded good results, most existing approaches optimize symmetric evaluation metrics and assume that all t...