The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
AndroDialysis: Analysis of Android Intent Effectiveness in Malware Detection
Open accessAbstract
The wide popularity of Android systems has been accompanied by increase in the number of malware targeting these systems. This is largely due to the open nature of the Android framework that facilitates the incorporation of third-party applications running on top of any Android device. Inter-process communication is one of the most notable features of the Android framework as it allows the reuse of components across process boundaries. This mechanism is used as gateway to access different sensitive services in the Android framework. In the Android platform, this communication system is usually driven by a late runtime binding messaging object known as Intent. In this paper, we evaluate the effectiveness of Android Intents (explicit and implicit) as a distinguishing feature for identifying malicious applications . We show that Intents are semantically rich features that are able to encode the intentions of malware when compared to other well-studied features such as permissions. We also argue that this type of feature is not the ultimate solution. It should be used in conjunction with other known features. We conducted experiments using a dataset containing 7406 applications that comprise 1846 clean and 5560 infected applications. The results show detection rate of 91% using Android Intent against 83% using Android permission. Additionally, experiment on combination of both features results in detection rate of 95.5%.
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Cites
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Drebin: Effective and Explainable Detection of Android Malware in Your Pocket
Arp, D., Spreitzenbarth, M., Hübner, M., Gascon, H., & Rieck, K. (2014) · Proceedings 2014 Network and Distributed System Security Symposium · doi:10.14722/ndss.2014.23247 · Cited by 2,331
Analyzing inter-application communication in Android
Chin, E., Felt, A. P., Greenwood, K., & Wagner, D. (2011) · Proceedings of the 9th international conference on Mobile systems, applications, and services · doi:10.1145/1999995.2000018 · Cited by 845
Hey, You, Get Off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets
Zhou, Y., Wang, Z., Zhou, W., & Jiang, X. (2012) · Network and Distributed System Security Symposium · Cited by 734
DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android
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PScout: analyzing the Android permission specification
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DroidMat: Android Malware Detection through Manifest and API Calls Tracing
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IccTA: Detecting Inter-Component Privacy Leaks in Android Apps
Li, L., Bartel, A., Bissyande, T. F., Klein, J., Le Traon, Y., Arzt, S., Rasthofer, S., Bodden, E., Octeau, D., & McDaniel, P. (2015) · 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering · doi:10.1109/icse.2015.48 · Cited by 608
RiskRanker: scalable and accurate zero-day android malware detection
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Metadata
- Authors
- Feizollah, A., Anuar, N. B., Salleh, R., Suarez-Tangil, G., & Furnell, S.
- Venue
- Computers & Security
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 65
- Pages
- 121-134
- ISSN
- 0167-4048 (ISSN-L)
- OpenAlex
- W2551095084
- Cited by
- 267
- References
- 41
- FWCI
- 26.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Feizollah, A., Anuar, N. B., Salleh, R., Suarez-Tangil, G., & Furnell, S. (2017). AndroDialysis: Analysis of Android Intent Effectiveness in Malware Detection. Computers & Security. https://doi.org/10.1016/j.cose.2016.11.007
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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