A Survey on Mobile Malware Detection Techniques-Reference-Cited by-同舟云学术

A Survey on Mobile Malware Detection Techniques

Published:2020-02-01 Issue:2 Volume:E103.D Page:204-211
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

KOULIARIDIS Vasileios¹,BARMPATSALOU Konstantia²,KAMBOURAKIS Georgios³,CHEN Shuhong⁴

Affiliation:

1. Department of Information & Communication Systems Engineering, University of Aegean

2. Centre for Informatics and Systems of the University of Coimbra

3. European Commission, Joint Research Centre (JRC)

4. Guangzhou University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E103.D/2/E103.D_2019INI0003/_pdf

Reference45 articles.

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2. [2] McAfee, “Mobile Threat Report,” https://www.mcafee.com/enterprise/en-us/assets/reports/rp-mobile-threat-report-2018.pdf, accessed May 10 2018.

3. [3] Symantec, “Motivations of Recent Android Malware,” http://www.symantec.com/content/en/us/enterprise/media/security_response/whitepapers/motivations_of_recent_android_malware.pdf, accessed Dec. 10 2018.

4. [4] P. Yan, Z. Yan, “A survey on dynamic mobile malware detection,” Softw. Qual. J., vol.26, no.3, pp.891-919, 2018. 10.1007/s11219-017-9368-4

5. [5] M. La Polla, F. Martinelli, and D. Sgandurra, “A Survey on Security for Mobile Devices,” IEEE Commun. Surv. Tutorials, vol.15, no.1, pp.446-471, 2013. 10.1109/surv.2012.013012.00028

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