Anomaly-based exploratory analysis and detection of exploits in android mediaserver

Guillermo Suarez-Tangil, Santanu Kumar Dash, P. García-Teodoro, J. Camacho, L. Cavallaro
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引用次数: 5

Abstract

Smartphone platforms are becoming increasingly complex, which gives way to software vulnerabilities difficult to identify and that might allow malware developers to gain unauthorised privileges through technical exploitation. However, the authors maintain that these types of attacks indirectly renders a number of unexpected behaviours in the system that can be profiled. In this work, the authors present CoME , an anomaly-based methodology aiming at detecting software exploitation in Android systems. CoME models the normal behaviour of a given software component or service and it is capable of identifying any unanticipated behaviour. To this end, they first monitor the normal operation of a given exploitable component through lightweight virtual introspection. Then, they use a multivariate analysis approach to estimate the normality model and detect anomalies. They evaluate their system against one of the most critical vulnerable and widely exploited services in Android, i.e. the mediaserver. Results show that the proposed approach can not only provide a meaningful explanatory of discriminant features for illegitimate activities, but can also be used to accurately detect malicious software exploitations at runtime.
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基于异常的android mediasserver漏洞探索性分析与检测
智能手机平台正变得越来越复杂,这给难以识别的软件漏洞让路,这可能使恶意软件开发人员通过技术利用获得未经授权的特权。然而,作者坚持认为,这些类型的攻击间接地在系统中呈现了许多可以被分析的意外行为。在这项工作中,作者提出了CoME,一种基于异常的方法,旨在检测Android系统中的软件利用。CoME为给定软件组件或服务的正常行为建模,并且能够识别任何意外行为。为此,它们首先通过轻量级虚拟自省监视给定可利用组件的正常操作。然后,他们使用多变量分析方法来估计正态性模型并检测异常。他们针对Android中最脆弱和被广泛利用的服务之一(即mediaserver)来评估他们的系统。结果表明,该方法不仅可以对非法活动的判别特征提供有意义的解释,而且可以用于在运行时准确检测恶意软件利用。
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