Detecting Android malware using Long Short-term Memory (LSTM)-Reference-Cited by-同舟云学术

Detecting Android malware using Long Short-term Memory (LSTM)

Published:2018-03-22 Issue:3 Volume:34 Page:1277-1288
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Vinayakumar R.¹,Soman K.P.¹,Poornachandran Prabaharan²,Sachin Kumar S.¹

Affiliation:

1. Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University, India

2. Center for Cyber Security and Networks, Amrita School of Engineering, Amritapuri, Amrita Vishwa Vidyapeetham, Amrita University, India

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference34 articles.

1. Andrubis-1,000,000 Apps Later: A view on current Android malware behaviors;Lindorfer;Third International Workshop on Building Analysis Datasets and Gathering Experience Returns for Security (BADGERS),2014

2. Oberheide J. and Miller C. , Dissecting the Android bouncer, SummerCon2012, New York, 2012.

3. From desktop to mobile: Examining the security experience;Botha;Computer & Security

4. Amos B. , Turner H. and White J. , Applying machine learning classifiers to dynamic Android malware detection at scale, 9th International Wireless Communications and Mobile Computing Conference (IWCMC), 2013, pp. 1666–1671.

5. Hunting for metamorphic;Szor;Virus,2001

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