Function-Oriented Mobile Malware Analysis as First Aid

摘要: Recently, highly well-crafted mobile malware has arisen as devices manage valuable and sensitive information. Currently, it is impossible to detect prevent all because the amount of new continues increase exponentially; detection methods need improve in order respond quickly effectively malware. For quick response, revealing main purpose or functions captured important; however, only few recent works have attempted find malware’s purpose. Our approach designed help with efficient effective incident responses countermeasure development by analyzing malicious behavior. In this paper, we propose a novel method for function-oriented analysis based on suspicious API call patterns. Instead extracting patterns each family, focus such certain functionalities. proposed dumps memory sections where an application allocated extracts sequences from bytecode comparing predefined lists. By matching our functionality database, determines whether they are malicious. The experiment results demonstrate that performs well detecting high accuracy.