Investigate Android Malware’s Behaviour Through Dynamic Analysis (Anserverbot)

Jeeva, Kumar (2013) Investigate Android Malware’s Behaviour Through Dynamic Analysis (Anserverbot). Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Nowadays, the growth of android-based Smartphone’s is growing rapidly and the unfortunate issue is that android malware too growing as rapid as well simultaneously. The popularity and adoption of Smartphone’s has greatly stimulated the spread of mobile malware, especially on the popular platforms such as Android. Malware or malicious software is software that is residing in a system and cause harm to the system. The most well-known android malwares such as DroidKungFu, Goldream, BeanBot and AnserverBot are the major threats to the users of the Smartphone’s. In light of their rapid growth, there is a pressing need to develop effective Therefore, analysis of the behavior of these malware attacks need to be studied in order to control the unwanted growth of android malware. That’s what this project is merely all about. Introducingly android malware analysis whereby it is a process in which the malwares’ code structure, operational and functionality are being analyzed deeply. The analysis consists of two types namely static analysis and dynamic analysis. The objectives of this project are to investigate the behavior of android malware through dynamic analysis, to identify and profile the behavior of android malware based on the parameter and lastly to differentiate the parameter of android during the infection and normal condition. In order for the project to be conducted and also to be completed in a right manner and correct sequence, there are total of five phases involved in the project methodology. The phases are in ascending sequence which are literature review, analysis, design and development, implementation and lastly testing and evaluation phases. The expected outcomes would be the results from disassembly malwares will varies and gain a clear understanding in identify the android malware’s behavior in order to imagine an effective measure that can be practically developed.

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