2015Unpublished venueRequires access

Obfuscation Techniques against Signature-Based Detection: A Case Study

Gerardo Canfora, Andrea Di Sorbo, Francesco Mercaldo, Corrado Aaron Visaggio

Open publisher page 57 citations

Abstract

Android malware is increasingly growing interms of complexity. In order to evade signature-based detection, which represents the most adopted technique by current antimalware vendors, malware writers begin to deploy malware with the ability to change their code as they propagate.In this paper, our aim is to evaluate the robustness of Android antimalware tools when various evasion techniques are used to obfuscate malicious payloads. To support this assessment we realized a tool which applies a number of common transformations on the code of malware applications, and applied these transformations to about 5000 malware apps. Our results demonstrate that, after the code transformations, the malware is not detected by a large set of antimalware tools,even when, before applying the transformations, malware was correctly identified by most antimalware tools. Such outcomes suggest that malware detection methods must be quickly re-designed for protecting successfully smart devices.

About this research paper

What this paper is about

Android malware is increasingly growing interms of complexity. In order to evade signature-based detection, which represents the most adopted technique by current antimalware vendors, malware writers begin to deploy malware with the ability to change their code as they propagate.In this paper, our aim is to evaluate the robustness of Android antimalware tools when various evasion techniques are used to obfuscate malicious payloads. To support this assessment we realized a tool which applies a number of common transformations on the code of malware applications, and applied these transformations to about 5000 malware apps. Our results demonstrate that, after the code transformations, the malware is not detected by a large set of antimalware tools,even when, before applying the transformations, malware was correctly identified by most antimalware tools. Such outcomes suggest that malware detection methods must be quickly re-designed for protecting successfully smart devices.

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OpenAlex reports 57 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Android malware is increasingly growing interms of complexity. In order to evade signature-based detection, which represents the most adopted technique by current antimalware vendors, malware writers begin to deploy malware with the ability to change their code as they propagate.In this paper, our aim is to evaluate the robustness of Android antimalware tools when various evasion techniques are used to obfuscate malicious payloads. To support this assessment we realized a tool which applies a number of common transformations on the code of malware applications, and applied these transformations to about 5000 malware apps. Our results demonstrate that, after the code transformations, the malware is not detected by a large set of antimalware tools,even when, before applying the transformations, malware was correctly identified by most antimalware tools. Such outcomes suggest that malware detection methods must be quickly re-designed for protecting successfully smart devices.

Key concepts: Malware, Cryptovirology, Computer science, Obfuscation, Android malware, Android (operating system), Evasion (ethics), Mobile malware

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