With the increased access of android based mobile devices in the mobile market, mobile malware mainly targets to infect the android platform through various infection routes. The rapidly increased number of android malware threats through malicious SMS messages, spam, malware-bearing advertisements, android malware analysis, and detection has become important for cyber security and malware forensics. Hence, with the target of improving security and facilitating malware forensics, android malware analysis has been widely focused on as an ongoing research area. Android malware analysis is predominantly integrated with the financial security, privacy, and malware forensics in the android platform.
   Nowadays, malicious attackers hide their activities through code obfuscations in the android system, resulting in the difficulty of malware analysis from the camouflage features. Hence, android malware analysis has become an imperative research area in the growing smartphone-assisted human life worldwide.
   In recent years, smartphone users have increasingly suffered from android malware such as stealing sensitive information, sending premium messages, and connecting to a control server with a remote command. To investigate the android malware, machine learning-based research works have emerged with the analysis of the static and dynamic patterns in the android operating system.