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

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

Publikováno v: IEEE Empirical Software Engineering
Empirical Software Engineering, 27(1):16, 1-41. Springer Netherlands
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 ', Empirical Software Engineering, vol. 27, no. 1, 16, pp. 1-41 . https://doi.org/10.1007/s10664-021-10013-5
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

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 apps, details about the g

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5ac95d02b056809df03c3dfaccc0be9
https://doi.org/10.18420/se2022-ws-020

Text/Conference Paper

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

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 abo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d7352cd41ed32a8e51d786e6e8224a2f

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High Order and Multilayer Perceptron Initialization

Autor: Thimm, Georg, Fiesler, Emile

Proper initialization is one of the most important prerequisites for fast convergence of feed-forward neural networks like high order and multilayer perceptrons. This publication aims at determining the optimal variance (or range) for the initial wei

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6e58e8974a279a149ad9ffbe65aa7410
https://infoscience.epfl.ch/record/82433