TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses

Linghui Luo; Felix Pauck; Goran Piskachev; Manuel Benz; Ivan Pashchenko; Martin Mory; Eric Bodden; Ben Hermann; Fabio Massacci

doi:10.18420/se2022-ws-020

TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses

Linghui Luo, Felix Pauck, Goran Piskachev, Manuel Benz, Ivan Pashchenko, Martin Mory, Eric Bodden, Ben Hermann, Fabio Massacci

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Due to the lack of established real-world benchmark suites for static taint analyses of Android applications, evaluations of these analyses are often restricted and hard to compare. Even in evaluations that do use real-world applications, details about the ground truth in those apps are rarely documented, which makes it difficult to compare and reproduce the results. Our recent study fills this gap. It first defines a set of sensible construction criteria for such a benchmark suite. It further proposes the TaintBench benchmark suite designed to fulfil these construction criteria. Along with the suite, this paper introduces the TaintBench framework, which allows tool-assisted benchmark suite construction, evaluation and inspection. Our experiments using TaintBench reveal new insights of popular Android taint analysis tools.

Original language	English
Title of host publication	Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik
Subtitle of host publication	[Proceedings]
Editors	Lars Grunske, Janet Siegmund, Andreas Vogelsang
Publisher	Gesellschaft fur Informatik (GI)
Pages	65-67
Number of pages	3
ISBN (Electronic)	9783885797142
DOIs	https://doi.org/10.18420/se2022-ws-020
Publication status	Published - 2022
Event	Fachtagung des GI-Fachbereichs Softwaretechnik, Software Engineering 2022 - Conference of the GI Software Engineering Section, Software Engineering 2022 - Virtual, Online, Germany Duration: 21 Feb 2022 → 25 Feb 2022

Publication series

Name	Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Volume	P-320
ISSN (Print)	1617-5468

Conference

Conference	Fachtagung des GI-Fachbereichs Softwaretechnik, Software Engineering 2022 - Conference of the GI Software Engineering Section, Software Engineering 2022
Country/Territory	Germany
City	Virtual, Online
Period	21/02/22 → 25/02/22

Bibliographical note

Publisher Copyright:
© 2022 Gesellschaft fur Informatik (GI). All rights reserved.

Keywords

Android malware
Benchmark
Real-world benchmark
Taint analysis

Access to Document

10.18420/se2022-ws-020

A1-20_TaintBench-Automatic RealWorld Malware Benchmarking of Android Taint AnalysesFinal published version, 291 KBLicence: CC BY

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Cite this

Luo, L., Pauck, F., Piskachev, G., Benz, M., Pashchenko, I., Mory, M., Bodden, E., Hermann, B., & Massacci, F. (2022). TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses. In L. Grunske, J. Siegmund, & A. Vogelsang (Eds.), Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik: [Proceedings] (pp. 65-67). Article A1-20 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-320). Gesellschaft fur Informatik (GI). https://doi.org/10.18420/se2022-ws-020

Luo, Linghui ; Pauck, Felix ; Piskachev, Goran et al. / TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses. Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik: [Proceedings]. editor / Lars Grunske ; Janet Siegmund ; Andreas Vogelsang. Gesellschaft fur Informatik (GI), 2022. pp. 65-67 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

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abstract = "Due to the lack of established real-world benchmark suites for static taint analyses of Android applications, evaluations of these analyses are often restricted and hard to compare. Even in evaluations that do use real-world applications, details about the ground truth in those apps are rarely documented, which makes it difficult to compare and reproduce the results. Our recent study fills this gap. It first defines a set of sensible construction criteria for such a benchmark suite. It further proposes the TaintBench benchmark suite designed to fulfil these construction criteria. Along with the suite, this paper introduces the TaintBench framework, which allows tool-assisted benchmark suite construction, evaluation and inspection. Our experiments using TaintBench reveal new insights of popular Android taint analysis tools.",

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author = "Linghui Luo and Felix Pauck and Goran Piskachev and Manuel Benz and Ivan Pashchenko and Martin Mory and Eric Bodden and Ben Hermann and Fabio Massacci",

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Luo, L, Pauck, F, Piskachev, G, Benz, M, Pashchenko, I, Mory, M, Bodden, E, Hermann, B & Massacci, F 2022, TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses. in L Grunske, J Siegmund & A Vogelsang (eds), Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik: [Proceedings]., A1-20, Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), vol. P-320, Gesellschaft fur Informatik (GI), pp. 65-67, Fachtagung des GI-Fachbereichs Softwaretechnik, Software Engineering 2022 - Conference of the GI Software Engineering Section, Software Engineering 2022, Virtual, Online, Germany, 21/02/22. https://doi.org/10.18420/se2022-ws-020

TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses. / Luo, Linghui; Pauck, Felix; Piskachev, Goran et al.
Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik: [Proceedings]. ed. / Lars Grunske; Janet Siegmund; Andreas Vogelsang. Gesellschaft fur Informatik (GI), 2022. p. 65-67 A1-20 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-320).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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T1 - TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses

AU - Luo, Linghui

AU - Pauck, Felix

AU - Piskachev, Goran

AU - Benz, Manuel

AU - Pashchenko, Ivan

AU - Mory, Martin

AU - Bodden, Eric

AU - Hermann, Ben

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Luo L, Pauck F, Piskachev G, Benz M, Pashchenko I, Mory M et al. TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses. In Grunske L, Siegmund J, Vogelsang A, editors, Software Engineering 2022 (SE 2022) - Fachtagung des GI-Fachbereichs Softwaretechnik: [Proceedings]. Gesellschaft fur Informatik (GI). 2022. p. 65-67. A1-20. (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)). Epub 2022 Feb 21. doi: 10.18420/se2022-ws-020

TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Persistent URL (handle)

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