Chatting Application Monitoring on Android System and its Detection based on the Correlation Test

Yafei Li, Jiageng Chen, A. Ho
{"title":"Chatting Application Monitoring on Android System and its Detection based on the Correlation Test","authors":"Yafei Li, Jiageng Chen, A. Ho","doi":"10.23919/APSIPA.2018.8659583","DOIUrl":null,"url":null,"abstract":"Mobile phones are playing an important roles in our modern digital society, which have already replaced the traditional computer in many situations. Nevertheless, the number of malicious software also starts to grow and showed significant impact on our legal use. Among several mobile systems, the Android platform is currently the most widely used and open system, which also makes it a very attractive target for the malicious applications. User privacy is of great interest to many different agents, which becomes of the most valuable target for the malware, and the chatting software naturally become one of the richest information resource target. In this paper, we first investigate the core techniques that are used by the most monitoring softwares. Then we propose several correlation experiments to efficiently detect the those softwares. We developed a monitoring prototype as well as the detecting system, including the mobile phone side and the remote web server side, to simulate the scenario in the real-world environment. The experiment confirmed the efficiency of our approach.","PeriodicalId":287799,"journal":{"name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/APSIPA.2018.8659583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Mobile phones are playing an important roles in our modern digital society, which have already replaced the traditional computer in many situations. Nevertheless, the number of malicious software also starts to grow and showed significant impact on our legal use. Among several mobile systems, the Android platform is currently the most widely used and open system, which also makes it a very attractive target for the malicious applications. User privacy is of great interest to many different agents, which becomes of the most valuable target for the malware, and the chatting software naturally become one of the richest information resource target. In this paper, we first investigate the core techniques that are used by the most monitoring softwares. Then we propose several correlation experiments to efficiently detect the those softwares. We developed a monitoring prototype as well as the detecting system, including the mobile phone side and the remote web server side, to simulate the scenario in the real-world environment. The experiment confirmed the efficiency of our approach.
基于相关测试的Android聊天应用监控及检测
手机在现代数字社会中扮演着重要的角色,在许多情况下已经取代了传统的电脑。然而,恶意软件的数量也开始增长,并对我们的合法使用产生了重大影响。在众多的移动系统中,Android平台是目前使用最广泛、最开放的系统,这也使其成为恶意应用程序的一个极具吸引力的目标。用户隐私是众多代理关注的焦点,成为恶意软件攻击的最有价值的目标,而聊天软件自然成为信息资源最丰富的目标之一。在本文中,我们首先研究了大多数监控软件使用的核心技术。然后,我们提出了一些相关实验来有效地检测这些软件。我们开发了一个监控原型和检测系统,包括手机端和远程web服务器端,以模拟现实环境中的场景。实验证实了我们方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信