摘要
To devise efficient approaches and tools for detecting malicious packages in the Android ecosystem, researchers are increasingly required to have a deep understanding of malware. There is thus a need to provide a framework for dissecting malware and locating malicious program fragments within app code in order to build a comprehensive dataset of malicious samples. Towards addressing this need, we propose in this work a tool-based approach called HookRanker, which provides ranked lists of potentially malicious packages based on the way malware behaviour code is triggered. With experiments on a ground truth of piggybacked apps, we are able to automatically locate the malicious packages from piggybacked Android apps with an accuracy@5 of 83.6% for such packages that are triggered through method invocations and an accuracy@5 of 82.2% for such packages that are triggered independently.
| 源语言 | 英语 |
|---|---|
| 页(从-至) | 1108-1124 |
| 页数 | 17 |
| 期刊 | Journal of Computer Science and Technology |
| 卷 | 32 |
| 期 | 6 |
| DOI | |
| 出版状态 | 已出版 - 1 11月 2017 |
| 已对外发布 | 是 |
学术指纹
探究 'On Locating Malicious Code in Piggybacked Android Apps' 的科研主题。它们共同构成独一无二的学术指纹。引用此
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