Journal of Information Security

Journal of Information Security

ISSN Print: 2153-1234
ISSN Online: 2153-1242
www.scirp.org/journal/jis
E-mail: jis@scirp.org
"Analysis of Malware Families on Android Mobiles: Detection Characteristics Recognizable by Ordinary Phone Users and How to Fix It"
written by Hieu Le Thanh,
published by Journal of Information Security, Vol.4 No.4, 2013
has been cited by the following article(s):
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[1] Malware detection with sequence-based machine learning and deep learning
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[2] Analysis of the Latest Trojans on Android Operating System
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[3] Android malware detection using static analysis, machine learning and deep learning
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[4] PACER: Platform for Android Malware Classification, Performance Evaluation and Threat Reporting
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[5] Proposed Framework to Improving Performance of Familial Classification in Android Malware
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[6] An Informative and Comprehensive Behavioral Characteristics Analysis Methodology of Android Application for Data Security in Brain-Machine Interfacing
2020
[7] Mobile Security: A Look into Android
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[8] Android Malware Family Classification and Analysis: Current Status and Future Directions
2020
[9] Malwares: Creation and Avoidance
2019
[10] Analysis of the Impact of Permissions on the Vulnerability of Mobile Applications
2019
[11] Survey Paper is on Android Malware Detection Using Deep Eigenspace Learning
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[12] PACE: Platform for Android Malware Classification and Performance Evaluation
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[13] Mobile Malware Classification
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[14] Hydra-Bite: Static Taint Immunity, Split and Complot Based Information Capture Method for Android Device
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[15] Permission-Set Based Detection and Analysis of Android Malware
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[16] Hydra-Bite: Static Taint Immunity, Split, and Complot Based Information Capture Method for Android Device
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[17] GENERAL ANDROID MALWARE BEHAVIOUR TAXONOMY
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[18] Permission Based in Android Malware Classification
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[19] A Survey on Android Malware Detection
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[20] A compendious investigation of Android malware family
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[21] DroidWard: An Effective Dynamic Analysis Method for Vetting Android Applications
Cluster Computing, 2016
[22] Enhancing mobile learning security
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[23] An Intelligent Methodology for Malware Detection in Android Smartphones Based Static Analysis
INTERNATIONAL JOURNAL OF COMMUNICATIONS, 2016
[24] The Trend of Mobile Malware and Effective Detection System
2016
[25] An Improved Feature Vector storage metric for fast Android Malware Detection Framework
IOSR Journal of Computer Engineering (IOSR-JCE), 2015
[26] A Review on: SMS Botnet Detection
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[27] DWroidDump: Executable Code Extraction from Android Applications for Malware Analysis
International Journal of Distributed Sensor Networks, 2015
[28] A Novel Approach to Detect Android Malware
Procedia Computer Science, 2015
[29] Structural information based malicious app similarity calculation and clustering
Proceedings of the 2015 Conference on research in adaptive and convergent systems, 2015
[30] Kullback-Leibler Divergence Based Detection of Repackaged Android Malware
2015
[31] Reduced Permissions Schema for Malware Detection in Android Smartphones
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[32] 휴리스틱 기반의 스미싱 파일분석 및 대응방법
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[33] The trend of mobile malwares and effective detection techniques
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[34] Risk Assessment of Network Distributed Android Applications
2014
[35] Techniques for analysing Android malware
Information and Communication Technology for The Muslim World (ICT4M), 2014 The 5th International Conference on, 2014
[36] DIAGNóSTICO DE ATAQUES DE SEGURIDAD MEDIANTE REDES BAYESIANAS
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[37] Detection of repackaged android malware
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