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Extractocol: Automatic Extraction of Application-level Protocol Behaviors for Android Applications

Published: 17 August 2015 Publication History

Abstract

No abstract available.

References

[1]
Free & open source app repository, https://f-droid.org.
[2]
S. Arzt, S. Rasthofer, C. Fritz, E. Bodden, A. Bartel, J. Klein, Y. Le Traon, D. Octeau, and P. McDaniel. Flowdroid: Precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for android apps. In Proc. ACM SIGPLAN PLDI, June 2014.
[3]
S. Dai, A. Tongaonkar, X. Wang, A. Nucci, and D. Song. Network profiler: Towards automatic fingerprinting of android apps. In Proc. IEEE INFOCOM, 2013.
[4]
N. K. R. M. T. M. R. G. Luis Pedrosa, Ari Fogel. Spa: A general framework for systematic protocol analysis. In Proc. USENIX NSDI, 2015.
[5]
L. Richardson and S. Ruby. Restful Web Services. O'Reilly, first edition, 2007.
[6]
A. Tongaonkar, R. Keralapura, and A. Nucci. Challenges in network application identification. In Proc. USENIX LEET, 2012.

Cited By

View all
  • (2018)Large-Scale Analysis of Remote Code Injection Attacks in Android AppsSecurity and Communication Networks10.1155/2018/24892142018Online publication date: 17-Apr-2018
  • (2016)Enabling Automatic Protocol Behavior Analysis for Android ApplicationsProceedings of the 12th International on Conference on emerging Networking EXperiments and Technologies10.1145/2999572.2999596(281-295)Online publication date: 6-Dec-2016
  • (2016)An end-user oriented tool suite for development of mobile applicationsProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering10.1145/2970276.2970279(768-773)Online publication date: 25-Aug-2016
  • Show More Cited By

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  1. Extractocol: Automatic Extraction of Application-level Protocol Behaviors for Android Applications

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      Information & Contributors

      Information

      Published In

      cover image ACM SIGCOMM Computer Communication Review
      ACM SIGCOMM Computer Communication Review  Volume 45, Issue 4
      SIGCOMM'15
      October 2015
      659 pages
      ISSN:0146-4833
      DOI:10.1145/2829988
      Issue’s Table of Contents
      • cover image ACM Conferences
        SIGCOMM '15: Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication
        August 2015
        684 pages
        ISBN:9781450335423
        DOI:10.1145/2785956
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 17 August 2015
      Published in SIGCOMM-CCR Volume 45, Issue 4

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      Author Tags

      1. android
      2. protocol behaviors
      3. static analysis

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      • Poster

      Funding Sources

      • National Research Foundation of Korea
      • Institute for Information communications Technology Promotion

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      Cited By

      View all
      • (2018)Large-Scale Analysis of Remote Code Injection Attacks in Android AppsSecurity and Communication Networks10.1155/2018/24892142018Online publication date: 17-Apr-2018
      • (2016)Enabling Automatic Protocol Behavior Analysis for Android ApplicationsProceedings of the 12th International on Conference on emerging Networking EXperiments and Technologies10.1145/2999572.2999596(281-295)Online publication date: 6-Dec-2016
      • (2016)An end-user oriented tool suite for development of mobile applicationsProceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering10.1145/2970276.2970279(768-773)Online publication date: 25-Aug-2016
      • (2016)Application-specific Acceleration Framework for Mobile ApplicationsProceedings of the 2016 ACM SIGCOMM Conference10.1145/2934872.2959049(559-560)Online publication date: 22-Aug-2016
      • (2024)DEMISTIFY: Identifying On-device Machine Learning Models Stealing and Reuse Vulnerabilities in Mobile AppsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623325(1-13)Online publication date: 20-May-2024
      • (2024)Attention! Your Copied Data is Under Monitoring: A Systematic Study of Clipboard Usage in Android AppsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623317(1-13)Online publication date: 20-May-2024
      • (2023)Detecting and Measuring Aggressive Location Harvesting in Mobile Apps via Data-flow Path EmbeddingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/35794477:1(1-27)Online publication date: 2-Mar-2023
      • (2022)PeriScopeProceedings of the 2022 ACM on Asia Conference on Computer and Communications Security10.1145/3488932.3517410(521-533)Online publication date: 30-May-2022
      • (2020)Automatic Uncovering of Hidden Behaviors From Input Validation in Mobile Apps2020 IEEE Symposium on Security and Privacy (SP)10.1109/SP40000.2020.00072(1106-1120)Online publication date: May-2020
      • (2020)MobiMVL: A Model-Driven Mobile Application Development Approach for End-UsersArtificial Intelligence and Security10.1007/978-3-030-57884-8_60(682-694)Online publication date: 1-Sep-2020
      • Show More Cited By

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