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Jean-Marie Mineau 2025-08-17 23:35:07 +02:00
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3_rasta/5_soa_comp.typ
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@ -12,7 +12,7 @@ These benchmarks confirmed that some tools such as Amandroid and Flowdroid are l
We confirm the hypothesis of Luo #etal that real-world applications lead to less efficient analysis than using hand crafted test applications or old datasets~@luoTaintBenchAutomaticRealworld2022.
In addition, even if Drebin is not hand-crafted, it is quite old seams to present similar issue as hand-crafted dataset when used to evaluate a tool: we obtained really good results compared to the Rasta dataset -- which is more representative of realworld applications.
Our finding are also consistent with the numerical results of Pauck #etal that showed that #mypercent(106, 180) of DIALDroid-Bench~@bosuCollusiveDataLeak2017 real-world applications are analyzed successfully with the 6 evaluated tools~@pauckAndroidTaintAnalysis2018.
Our finding are also consistent with the numerical results of Pauck #etal that showed that #mypercent(106, 180) of DIALDroid-Bench~@bosuCollusiveDataLeak2017 real-world applications are analysed successfully with the 6 evaluated tools~@pauckAndroidTaintAnalysis2018.
Six years after the release of DIALDroid-Bench, we obtain a lower ratio of #mypercent(40.05, 100) for the same set of 6 tools but using the Rasta dataset of #NBTOTALSTRING applications.
We extended this result to a set of #nbtoolsvariationsrun tools and obtained a global success rate of #resultratio.
We confirmed that most tools require a significant amount of work to get them running~@reaves_droid_2016.