metal learning for malware classification

With the emergence of smartphones, Android has become a widely used mobile operating system. However, it is vulnerable whenencountering various types of attacks. Every day, new malware threatens the security of users’ devices and private data. Many methodshave been proposed to classify malicious applications, utilizing static or dynamic analysis for classification. However, previous methodsstill suffer from unsatisfactory performance due to two challenges