Mobile Malware Security Challeges and Cloud-Based Detection

被引:0
|
作者
Penning, Nicholas [1 ]
Hoffman, Michael [1 ]
Nikolai, Jason [1 ]
Wang, Yong [1 ]
机构
[1] Dakota State Univ, Coll Business & Informat Syst, Madison, SD 57042 USA
关键词
mobile; malware; security; detection; cloud; Android;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Mobile malware has gained significant ground since the dawning of smartphones and handheld devices. TrendLabs estimated that there were 718,000 malicious and high risk Android apps in the second quarter of 2013. Mobile malware malicious infections arise through various techniques such as installing repackaged legitimate apps with malware, updating current apps that piggy back malicious variants, or even a drive-by download. The infections themselves will perform at least one or multiple of the following techniques, privilege escalation, remote control, financial charge, and information collection, etc. This paper summarizes mobile malware threats and attacks, cybercriminal motivations behind malware, existing prevention methods and their limitations, and challenges encountered when preventing malware on mobile devices. The paper further proposes a cloud-based framework for mobile malware detection. The proposed framework requires a collaboration among mobile subscribers, app stores, and IT security professionals. The cloud-based malware detection is a promising approach towards mobile security.
引用
收藏
页码:181 / 188
页数:8
相关论文
共 50 条
  • [1] Cloud-Based Malware Detection Game for Mobile Devices with Offloading
    Xiao, Liang
    Li, Yanda
    Huang, Xueli
    Du, XiaoJiang
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2017, 16 (10) : 2742 - 2750
  • [2] Reinforcement Learning Based Mobile Offloading for Cloud-based Malware Detection
    Wan, Xiaoyue
    Sheng, Geyi
    Li, Yanda
    Xiao, Liang
    Du, Xiaojiang
    [J]. GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, 2017,
  • [3] PHOENIX: A Cloud-based Framework for Ensemble Malware Detection
    Bernardinetti, Giorgio
    Caporaso, Pasquale
    Di Cristofaro, Dimitri
    Quaglia, Francesco
    Bianchi, Giuseppe
    [J]. 2023 21ST MEDITERRANEAN COMMUNICATION AND COMPUTER NETWORKING CONFERENCE, MEDCOMNET, 2023, : 11 - 14
  • [4] ScanMe Mobile: A Cloud-based Android Malware Analysis Service
    Zhang, Hanlin
    Cole, Yevgeniy
    Ge, Linqiang
    Wei, Sixiao
    Yu, Wei
    Lu, Chao
    Chen, Genshe
    Shen, Dan
    Blasch, Erik
    Pham, Khanh D.
    [J]. APPLIED COMPUTING REVIEW, 2016, 16 (01): : 36 - 49
  • [5] Cloud-based Android Botnet Malware Detection System
    Jadhav, Suyash
    Dutia, Shobhit
    Calangutkar, Kedarnath
    Oh, Tae
    Kim, Young Ho
    Kim, Joeng Nyeo
    [J]. 2015 17TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT), 2015, : 347 - 352
  • [6] SECURITY ASPECTS OF CLOUD-BASED MOBILE LEARNING
    Velev, D. G.
    [J]. FINANCIAL AND CREDIT ACTIVITY-PROBLEMS OF THEORY AND PRACTICE, 2014, 2 (17): : 240 - 251
  • [7] PriMal: Cloud-Based Privacy-Preserving Malware Detection
    Sun, Hao
    Su, Jinshu
    Wang, Xiaofeng
    Chen, Rongmao
    Liu, Yujing
    Hu, Qiaolin
    [J]. INFORMATION SECURITY AND PRIVACY, ACISP 2017, PT II, 2017, 10343 : 153 - 172
  • [8] ThinAV: Truly Lightweight Mobile Cloud-based Anti-malware
    Jarabek, Chris
    Barrera, David
    Aycock, John
    [J]. 28TH ANNUAL COMPUTER SECURITY APPLICATIONS CONFERENCE (ACSAC 2012), 2012, : 209 - 218
  • [9] Research on Cloud-Based on Web Application Malware Detection Methods
    Kim, Ki-Hwan
    Lee, Dong-Il
    Shin, Yong-Tae
    [J]. ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING, 2018, 474 : 817 - 822
  • [10] Cloud-Based Malware Detection of Smart Meters in Advanced Metering Infrastructure
    Jian, Zuo
    Cai, Ziwen
    Qian, Bin
    Xiao, Yong
    [J]. Engineering Intelligent Systems, 2022, 30 (03): : 195 - 200