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首页> 外文会议>Working Conference on Mining Software Repositories >Euphony: Harmonious Unification of Cacophonous Anti-Virus Vendor Labels for Android Malware
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Euphony: Harmonious Unification of Cacophonous Anti-Virus Vendor Labels for Android Malware

机译：Euphony：适用于Android恶意软件的Cacophonous反病毒供应商标签的和谐统一

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摘要

Android malware is now pervasive and evolving rapidly. Thousands of malware samples are discovered every day with new models of attacks. The growth of these threats has come hand in hand with the proliferation of collective repositories sharing the latest specimens. Having access to a large number of samples opens new research directions aiming at efficiently vetting apps. However, automatically inferring a reference ground-truth from those repositories is not straightforward and can inadvertently lead to unforeseen misconceptions. On the one hand, samples are often mis-labeled as different parties use distinct naming schemes for the same sample. On the other hand, samples are frequently mis-classified due to conceptual errors made during labeling processes. In this paper, we analyze the associations between all labels given by different vendors and we propose a system called EUPHONY to systematically unify common samples into family groups. The key novelty of our approach is that no a-priori knowledge on malware families is needed. We evaluate our approach using reference datasets and more than 0.4 million additional samples outside of these datasets. Results show that EUPHONY provides competitive performance against the state-of-the-art.
机译：Android恶意软件现在无处不在，并且发展迅速。每天都会通过新的攻击模型发现成千上万的恶意软件样本。这些威胁的增长与共享最新样本的集体存储库的激增齐头并进。可以访问大量样本打开了旨在有效审查应用程序的新研究方向。但是，从这些存储库自动推断出参考事实并非易事，并且可能会无意间导致无法预料的误解。一方面，由于不同的参与方对同一样本使用不同的命名方案，因此样本经常被错误地标记。另一方面，由于在标记过程中发生概念错误，样本经常被错误分类。在本文中，我们分析了不同供应商提供的所有标签之间的关联，并提出了一个名为EUPHONY的系统，以将常见样本系统地统一到族群中。我们方法的关键新颖之处在于，不需要有关恶意软件系列的先验知识。我们使用参考数据集和这些数据集之外的40万多个其他样本来评估我们的方法。结果表明，EUPHONY与最先进的产品相比具有竞争优势。

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