Jicer: Simplifying Cooperative Android App Analysis Tasks

Pauck, Felix; Wehrheim, Heike

doi:10.26226/morressier.613b54401459512fce6a7d01

Cited by 1 publication

(3 citation statements)

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“…It first triggers all activities in a simulator, records the code invoked by each activity, and slices the target activity according to the recorded content. Jicer [41] is a work to perform general Android static slicing. It aims at slicing the code of any App with any slicing criterion.…”

Section: Android Slicingmentioning

confidence: 99%

“…The slicer's accuracy depends on its sensitivity regarding various program features [41]. A flow-sensitive slicer takes control dependencies into full consideration.…”

Section: Android Slicingmentioning

confidence: 99%

“…Second, the dynamic code slicing [10] needs human involvement, while the success rate of static code slicing is not high. We find that the Android slicing tool Jicer [41] cannot extract runnable IO processing codes for model testing purpose.…”

Section: Introductionmentioning

confidence: 95%

See 2 more Smart Citations

Automation Slicing and Testing for in-App Deep Learning Models

Wu¹,

Gong²,

Ke³

et al. 2022

Preprint

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Intelligent Apps (iApps), equipped with in-App deep learning (DL) models, are emerging to offer stable DL inference services. However, App marketplaces have trouble auto testing iApps because the in-App model is black-box and couples with ordinary codes. In this work, we propose an automated tool, ASTM, which can enable largescale testing of in-App models. ASTM takes as input an iApps, and the outputs can replace the in-App model as the test object. ASTM proposes two reconstruction techniques to translate the in-App model to a backpropagation-enabled version and reconstruct the IO processing code for DL inference. With the ASTM's help, we perform a large-scale study on the robustness of 100 unique commercial in-App models and find that 56% of in-App models are vulnerable to robustness issues in our context. ASTM also detects physical attacks against three representative iApps that may cause economic losses and security issues.

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Section: Android Slicingmentioning

confidence: 99%

“…The slicer's accuracy depends on its sensitivity regarding various program features [41]. A flow-sensitive slicer takes control dependencies into full consideration.…”

Section: Android Slicingmentioning

confidence: 99%