Andrana: Quick and Accurate Malware Detection for Android-Reference-Cited by-同舟云学术

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Andrana: Quick and Accurate Malware Detection for Android

Published:2016-12-29 Issue: Volume: Page:20-35
ISSN:0302-9743
Container-title:Foundations and Practice of Security
language:
Short-container-title:

Author:

Bedford Andrew,Garvin Sébastien,Desharnais Josée,Tawbi Nadia,Ajakan Hana,Audet Frédéric,Lebel Bernard

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-51966-1_2

Reference34 articles.

1. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;Y Aafer,2013

2. Android operating system security. http://developer.android.com/guide/topics/security/permissions.html . Accessed 5 July 2016

3. Apktool. https://ibotpeaches.github.io/Apktool/ . Accessed 5 July 2016

4. Appbrain. http://www.appbrain.com/stats/number-of-android-apps . Accessed 18 July 2016

5. Apvrille, A., Nigam, R.: Obfuscation in android malware, and how to fight back. Virus Bull. 1–10 (2014)

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1. GENDroid - a graph-based ensemble classifier for detecting Android malware;International Journal of Information and Computer Security;2022

2. DIMDA: Deep Learning and Image-Based Malware Detection for Android;Futuristic Trends in Networks and Computing Technologies;2022

3. Predicting the Impact of Android Malicious Samples Via Machine Learning;Second International Conference on Sustainable Technologies for Computational Intelligence;2021-10-19

4. Toward Semantic-Based Android Malware Detection Using Model Checking and Machine Learning;Lecture Notes in Computer Science;2021

5. DroidAutoML: A Microservice Architecture to Automate the Evaluation of Android Machine Learning Detection Systems;Distributed Applications and Interoperable Systems;2020

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