3 Search Results for "Uchitel, Sebastian"

Document
Replication Paper
DOI: 10.4230/LIPIcs.ECOOP.2025.40
Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification (Replication Paper)

Authors: Francisco Handrick Tomaz da Costa, Ismael Medeiros, Leandro Oliveira, João Calássio, Rodrigo Bonifácio, Krishna Narasimhan, Mira Mezini, and Márcio Ribeiro

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in mobile applications, particularly targeting the Android platform - the most popular mobile operating system. For this reason, several techniques have been proposed to identify malicious behavior in Android applications, including the Mining Android Sandbox approach (MAS approach), which aims to identify malicious behavior in repackaged Android applications (apps). However, previous empirical studies evaluated the MAS approach using a small dataset consisting of only 102 pairs of original and repackaged apps. This limitation raises questions about the external validity of their findings and whether the MAS approach can be generalized to larger datasets. To address these concerns, this paper presents the results of a replication study focused on evaluating the performance of the MAS approach regarding its capabilities of correctly classifying malware from different families. Unlike previous studies, our research employs a dataset that is an order of magnitude larger, comprising 4,076 pairs of apps covering a more diverse range of Android malware families. Surprisingly, our findings indicate a poor performance of the MAS approach for identifying malware, with the F1-score decreasing from 0.90 for the small dataset used in the previous studies to 0.54 in our more extensive dataset. Upon closer examination, we discovered that certain malware families partially account for the low accuracy of the MAS approach, which fails to classify a repackaged version of an app as malware correctly. Our findings highlight the limitations of the MAS approach, particularly when scaled, and underscore the importance of complementing it with other techniques to detect a broader range of malware effectively. This opens avenues for further discussion on addressing the blind spots that affect the accuracy of the MAS approach.
Cite as

Francisco Handrick Tomaz da Costa, Ismael Medeiros, Leandro Oliveira, João Calássio, Rodrigo Bonifácio, Krishna Narasimhan, Mira Mezini, and Márcio Ribeiro. Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification (Replication Paper). In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 40:1-40:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{handricktomazdacosta_et_al:LIPIcs.ECOOP.2025.40,
  author =	{Handrick Tomaz da Costa, Francisco and Medeiros, Ismael and Oliveira, Leandro and Cal\'{a}ssio, Jo\~{a}o and Bonif\'{a}cio, Rodrigo and Narasimhan, Krishna and Mezini, Mira and Ribeiro, M\'{a}rcio},
  title =	{{Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{40:1--40:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.40},
  URN =		{urn:nbn:de:0030-drops-233320},
  doi =		{10.4230/LIPIcs.ECOOP.2025.40},
  annote =	{Keywords: Android Malware Detection, Dynamic Analysis, Mining Android Sandboxes}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2011.106
An Inductive Approach for Modal Transition System Refinement

Authors: Dalal Alrajeh, Jeff Kramer, Alessandra Russo, and Sebastian Uchitel

Published in: LIPIcs, Volume 11, Technical Communications of the 27th International Conference on Logic Programming (ICLP'11) (2011)

Abstract
Modal Transition Systems (MTSs) provide an appropriate framework for modelling software behaviour when only a partial specification is available. A key characteristic of an MTS is that it explicitly models events that a system is required to provide and is proscribed from exhibiting, and those for which no specification is available, called maybe events. Incremental elaboration of maybe events into either required or proscribed events can be seen as a process of MTS refinement, resulting from extending a given partial specification with more information about the system behaviour. This paper focuses on providing automated support for computing strong refinements of an MTS with respect to event traces that describe required and proscribed behaviours using a non-monotonic inductive logic programming technique. A real case study is used to illustrate the practical application of the approach.
Cite as

Dalal Alrajeh, Jeff Kramer, Alessandra Russo, and Sebastian Uchitel. An Inductive Approach for Modal Transition System Refinement. In Technical Communications of the 27th International Conference on Logic Programming (ICLP'11). Leibniz International Proceedings in Informatics (LIPIcs), Volume 11, pp. 106-116, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

Copy BibTex To Clipboard

@InProceedings{alrajeh_et_al:LIPIcs.ICLP.2011.106,
  author =	{Alrajeh, Dalal and Kramer, Jeff and Russo, Alessandra and Uchitel, Sebastian},
  title =	{{An Inductive Approach for Modal Transition System Refinement}},
  booktitle =	{Technical Communications of the 27th International Conference on Logic Programming (ICLP'11)},
  pages =	{106--116},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-31-6},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{11},
  editor =	{Gallagher, John P. and Gelfond, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2011.106},
  URN =		{urn:nbn:de:0030-drops-31758},
  doi =		{10.4230/LIPIcs.ICLP.2011.106},
  annote =	{Keywords: Modal Transition Systems, Refinement, Inductive Logic Programming, Event Calculus}
}
Document
DOI: 10.4230/DagSemProc.06351.9
Partial Behavioural Models for Requirements and Early Design

Authors: Marsha Chechik, Greg Brunet, Dario Fischbein, and Sebastian Uchitel

Published in: Dagstuhl Seminar Proceedings, Volume 6351, Methods for Modelling Software Systems (MMOSS) (2007)

Abstract
The talk will discuss the problem of creation, management, and specifically merging of partial behavioural models, expressed as model transition systems. We argue why this formalism is essential in the early stages of the software cycle and then discuss why and how to merge information coming from different sources using this formalism. The talk is based on papers presented in FSE'04 and FME'06 and will also include emerging results on synthesizing partial behavioural models from temporal properties and scenarios.
Cite as

Marsha Chechik, Greg Brunet, Dario Fischbein, and Sebastian Uchitel. Partial Behavioural Models for Requirements and Early Design. In Methods for Modelling Software Systems (MMOSS). Dagstuhl Seminar Proceedings, Volume 6351, pp. 1-10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

Copy BibTex To Clipboard

@InProceedings{chechik_et_al:DagSemProc.06351.9,
  author =	{Chechik, Marsha and Brunet, Greg and Fischbein, Dario and Uchitel, Sebastian},
  title =	{{Partial Behavioural Models for Requirements and Early Design}},
  booktitle =	{Methods for Modelling Software Systems (MMOSS)},
  pages =	{1--10},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{6351},
  editor =	{Ed Brinksma and David Harel and Angelika Mader and Perdita Stevens and Roel Wieringa},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06351.9},
  URN =		{urn:nbn:de:0030-drops-8582},
  doi =		{10.4230/DagSemProc.06351.9},
  annote =	{Keywords: Requirements behavioural models}
}
  • Refine by Type
  • 3 Document/PDF
  • 1 Document/HTML

  • Refine by Publication Year
  • 1 2025
  • 1 2011
  • 1 2007

  • Refine by Author
  • 2 Uchitel, Sebastian
  • 1 Alrajeh, Dalal
  • 1 Bonifácio, Rodrigo
  • 1 Brunet, Greg
  • 1 Calássio, João
  • Show More...

  • Refine by Series/Journal
  • 2 LIPIcs
  • 1 DagSemProc

  • Refine by Classification
  • 1 Security and privacy → Malware and its mitigation

  • Refine by Keyword
  • 1 Android Malware Detection
  • 1 Dynamic Analysis
  • 1 Event Calculus
  • 1 Inductive Logic Programming
  • 1 Mining Android Sandboxes
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact