curious-monkey: evolved monkey for triggering malicious payloads in android malware

Dynamic analysis is a prominent approach in analyzing the behavior of android apps. to perform dynamic analysis, we need an event generator to provide proper environment for executing the app in an emulator. monkey is the most popular event generator for android apps in general, and is used in dynamic analysis of android malware as well. monkey provides high code coverage and yet high speed in generating events. however, in the case of malware analysis, monkey suers from several limitations. it only considers ui events but no system events, and because of random behavior in generating ui events, it may lose dropping the connectivity of the test environment during the analysis process. moreover, it provides no defense against malware evasion techniques. in this paper, we try to enhance monkey by reducing its limitations while preserving its advantages. the proposed approach has been implemented as an extended version of monkey, named curious-monkey. curious-monkey provides facilities for handling system events, handling evasion techniques, and keeping the test environment's connectivity up during the analysis process. we conducted many experiments to evaluate the eectiveness of the proposed tool regarding two important criteria in dynamic malware analysis: the ability to trigger malicious payloads and the code coverage. in the evaluation process, we used the evadroid benchmark and the amd malware data-set. moreover, we compared curious-monkey with monkey and ares tools. the results show that the curious-monkey provides better results in case of triggering malicious payloads, as well as better code coverage.