InviSeal: A Stealthy Dynamic Analysis Framework for Android Systems

Digital Threats: Research and Practice(2022)

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摘要
With wide adaptation of open-source Android into mobile devices by different device vendors, sophisticated malware are developed to exploit security vulnerabilities. As comprehensive security analysis on physical devices are impractical and costly, emulator driven security analysis has gained popularity in recent times. Existing dynamic analysis frameworks suffer from two major issues: (i) they do not provide foolproof anti-emulation-detection measures even for fingerprint-based attacks, and (ii) lack efficient cross-layer profiling capabilities. In this work, we present InviSeal, a comprehensive and scalable dynamic analysis framework that includes low-overhead cross-layer profiling techniques and detailed anti-emulation-detection measures along with the basic emulation features. While providing an emulator-based comprehensive analysis platform, InviSeal strives to remain behind-the-scene to avoid emulation-detection. We empirically demonstrate that the proposed OS layer profiling utility to achieve cross-layer profiling is ∼ 1.26X faster than existing strace -based approaches. Overall, on average, InviSeal incurs ∼ 1.04X profiling overhead in terms of the number of operations performed by the various workloads of the CaffeineMark-3.0 benchmark, which is better than the contemporary techniques. Furthermore, we measure the anti-emulation-detection strategies of InviSeal against the fingerprint-based emulation-detection attacks. Experimental results show that the emulation-detection attacks carried out by the malware samples do not find InviSeal as an emulated platform.
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stealthy dynamic analysis framework
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