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Apposcopy: automated detection of Android malware (invited talk)

Published: 17 November 2014 Publication History

Abstract

We present Apposcopy, a new semantics-based approach for detecting Android malware that steal private information. Apposcopy incorporates (i) a high-level language for specifying malware signatures and (ii) a static analysis for deciding if a given application matches a given signature. We have evaluated Apposcopy on a corpus of real-world Android applications and show that it can effectively pinpoint malicious applications that belong to certain malware families.

References

[1]
Android malware genome project. http://www.malgenomeproject.org/.
[2]
ProGuard. http://proguard.sourceforge.net/.
[3]
Q2 IT evolution threat report. http://tinyurl.com/lcg3ojb.
[4]
VirusTotal. https://www.virustotal.com/en/.
[5]
W. Enck, P. Gilbert, B. gon Chun, L. P. Cox, J. Jung, P. McDaniel, and A. Sheth. TaintDroid: An information-flow tracking system for realtime privacy monitoring on smartphones. In OSDI, pages 393–407, 2010.
[6]
Y. Feng, S. Anand, I. Dillig, and A. Aiken. Apposcopy: Semantics-based detection of android malware through static analysis. In SIGSOFT FSE, 2014.

Cited By

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  • (2023)Scalable Compositional Static Taint Analysis for Sensitive Data Tracing on Industrial Micro-ServicesProceedings of the 45th International Conference on Software Engineering: Software Engineering in Practice10.1109/ICSE-SEIP58684.2023.00015(110-121)Online publication date: 17-May-2023
  • (2022)A Deep Learning Method for Android Application Classification Using Semantic FeaturesSecurity and Communication Networks10.1155/2022/12891752022Online publication date: 1-Jan-2022
  • (2022)Benchmark Fuzzing for Android Taint Analyses2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM55253.2022.00007(12-23)Online publication date: Oct-2022
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  1. Apposcopy: automated detection of Android malware (invited talk)

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    Published In

    cover image ACM Conferences
    DeMobile 2014: Proceedings of the 2nd International Workshop on Software Development Lifecycle for Mobile
    November 2014
    18 pages
    ISBN:9781450332255
    DOI:10.1145/2661694
    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.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 November 2014

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    Author Tags

    1. Android
    2. Inter-component Call Graph
    3. Taint Analysis

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    Cited By

    View all
    • (2023)Scalable Compositional Static Taint Analysis for Sensitive Data Tracing on Industrial Micro-ServicesProceedings of the 45th International Conference on Software Engineering: Software Engineering in Practice10.1109/ICSE-SEIP58684.2023.00015(110-121)Online publication date: 17-May-2023
    • (2022)A Deep Learning Method for Android Application Classification Using Semantic FeaturesSecurity and Communication Networks10.1155/2022/12891752022Online publication date: 1-Jan-2022
    • (2022)Benchmark Fuzzing for Android Taint Analyses2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM55253.2022.00007(12-23)Online publication date: Oct-2022
    • (2021)Jicer: Simplifying Cooperative Android App Analysis Tasks2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)10.1109/SCAM52516.2021.00031(187-197)Online publication date: Sep-2021
    • (2021)Malicious application detection in android — A systematic literature reviewComputer Science Review10.1016/j.cosrev.2021.10037340(100373)Online publication date: May-2021
    • (2020)Deep Feature Extraction and Classification of Android Malware ImagesSensors10.3390/s2024701320:24(7013)Online publication date: 8-Dec-2020
    • (2019)Together strong: cooperative Android app analysisProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338915(374-384)Online publication date: 12-Aug-2019
    • (2018)Do Android taint analysis tools keep their promises?Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3236024.3236029(331-341)Online publication date: 26-Oct-2018

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