Towards Behavior-Based Analysis of Android Obfuscated Malware


연구 분야: Safety



학회: European Conference on Software Architecture


초록

In this paper, we report on the initial results of an ongoing project that aims to rigorously detect obfuscated Android malware. In fact, the detection of Android malware has become increasingly complex as malicious app developers employ various obfuscation techniques. Previous approaches have focused on addressing specific obfuscation methods, but the dynamic nature of these techniques presents challenges in accounting for all possible variations. In response to this challenge, we have developed an innovative behavioral methodology for analyzing obfuscated malware. Our approach combines model-based and AI-based techniques, making it the first effort to integrate these approaches for obfuscated malware detection. Given that deobfuscation is a computationally very challenging (i.e., NP-hard) problem, our methodology circumvents obfuscation by indirectly observing malware behavior through the runtime behavior of target services controlled and operated by the Android applications.


Author Profile
Zakaria Sawadogo

Gaston Berger University Saint-Louis Senegal

Senegal
Author Profile
Muhammad Taimoor Khan

Centre for Sustainable Cyber Security University of Greenwich London UK

정보 없음
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George Loukas

Cheikh Anta Diop University Dakar Senegal

Senegal

📄 논문 정보

발행 연도 2024년
인용수 0
출판 국가 Senegal
사이트 Springer
좋아요 수 0

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