Android Apps Dynamic Analysis

Android Apps Dynamic Analysis

android project app ideas 2019

Study results.The data directory (data) includes the rawdata of our study along with the results presented in theresearch paper. The data on metrics in three dimensions(General/Structure,ICC, andSecurity) is placed in therespective folder. R scripts for producing final results fromthe raw data in each folder are included accordingly. Eachraw data file is explainedhere, and the purpose of each Rscript is explainedhere. A convenience scriptproduceall.shisincluded underdatafor processing all the raw data at once.Benchmark suites.Our study used two benchmark suites:a suite of 125 individual apps and a suite of 62 apppairs that actually communicate at runtime as quicklytriggered by random inputs from Monkey [4]. The firstsuite can be readily downloaded from Google Play usingour helper scripts. The list of these apps is included (indata/benchmarks/used-benig-apps-droidfax.txt).The second suite is even more worthy of sharing becausefinding a set of apps with dynamically communicating peersis not trivial. android project app ideas 2019 This suite is particularly useful for evaluatingan inter-app dynamic analysis for Android. We have notonly provided the pairs but also the statistics on the ICCsthat linked them at runtime in our study (as detailed indata/benchmarks/app-pair-statistics.html).Characterization metrics.We defined a set of 122 metricsin the three dimensions mentioned above. These metrics havebeen used for discovering new insights into the behavioraltraits of Android apps in our study. Furthermore, they havebeen utilized for developing advanced malware classifiers aswell (based on the behavioral profile, defined by these metrics,of benign apps versus malware) [5]. These metrics (detailedhere) can be used by others for understanding app behaviorsand reused for future studies and techniques.