Detection of Malicious Applications on Android OS

被引:0
|
作者
Di Cerbo, Francesco [1 ]
Girardello, Andrea [2 ]
Michahelles, Florian [2 ]
Voronkova, Svetlana [1 ]
机构
[1] Free Univ Bolzano Bozen, Ctr Appl Software Engn, Bolzano, Italy
[2] ETH, Informat Management, Zurich, Switzerland
来源
COMPUTATIONAL FORENSICS | 2011年 / 6540卷
关键词
Mobile Forensics; Android OS; Security;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper presents a methodology for mobile forensics analysis, to detect "malicious" (or "malware") applications, i.e., those that deceive users hiding some of their functionalities. This methodology is specifically targeted for the Android mobile operating system, and relies on its security model features, namely the set of permissions exposed by each application. The methodology has been trained on more than 13,000 applications hosted on the Android Market, collected with AppAware. A case study is presented as a preliminary validation of the methodology.
引用
收藏
页码:138 / +
页数:3
相关论文
共 50 条
  • [21] ApkClassiFy: Identification and Classification of packed Android Malicious Applications
    Guo, Xu
    Zheng, Tao
    Chen, Xingshu
    Wang, Qixu
    Shao, Jiang
    Hu, Zhijie
    2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, : 2092 - 2097
  • [22] A Novel Approach to Restrict the Access of Malicious Applications in Android
    Dar, Muneer Ahmad
    2017 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION, EMBEDDED AND COMMUNICATION SYSTEMS (ICIIECS), 2017,
  • [23] Detecting Malicious Android Applications from Runtime Behavior
    Lageman, Nathaniel
    Lindsey, Mark
    Glodek, William
    2015 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM 2015), 2015, : 324 - 329
  • [24] DroidMalHunter: A Novel Entropy-based Anomaly Detection System to Detect Malicious Android Applications
    Ghaffari, Fariba
    Abadi, Mahdi
    2015 5TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE), 2015, : 301 - 306
  • [25] MsDroid: Identifying Malicious Snippets for Android Malware Detection
    He, Yiling
    Li, Yiping
    Wu, Lei
    Yang, Ziqi
    Ren, Kui
    Qin, Zhan
    IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2023, 20 (03) : 2025 - 2039
  • [26] A Review of Static Detection Methods for Android Malicious Application
    Pan J.
    Cui Z.
    Lin G.
    Chen X.
    Zheng L.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2023, 60 (08): : 1875 - 1894
  • [27] Malicious Android Application Detection Based on Composite Features
    Xiao, Jingxu
    Xu, Kaiyong
    Duan, Jialiang
    PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2019), 2019,
  • [28] Malicious application detection in android - A systematic literature review
    Sharma, Tejpal
    Rattan, Dhavleesh
    COMPUTER SCIENCE REVIEW, 2021, 40
  • [29] Malicious Application Detection and Classification System for Android Mobiles
    Malik, Sapna
    Khatter, Kiran
    INTERNATIONAL JOURNAL OF AMBIENT COMPUTING AND INTELLIGENCE, 2018, 9 (01) : 95 - 114
  • [30] Network-based detection of Android malicious apps
    Shree Garg
    Sateesh K. Peddoju
    Anil K. Sarje
    International Journal of Information Security, 2017, 16 : 385 - 400