Due to the existence of malware samples in large amounts of data, malware detection techniques are introduced. Machine learning techniques are applied to classify applications focused on malware detection. Android has seen impressive growth in the smartphone space. So, to overcome this problem, it is better to group malware samples with structural similarities. Clustering technique in Android applications is an important technique in machine learning and provides automatic classification of applications by classifying malware. Clustering keeps similar applications in a cluster and provides good results with information retrieval. The following steps can be included in the application clustering process: 1. The Android Manifest le specifies the permissions needed by the application. These files require permission to access limited items such as hardware devices and Android OS contacts. Clustering algorithms such as hierarchical and partitioning-based clustering such as K-Means or K-Medoids are used to cluster malware behavior. Various clustering algorithms are discussed...