Investigation of Malware Detection Techniques on Smart Phones

G. Shanmugasundaram, S. Balaji, T. Mugilan
{"title":"Investigation of Malware Detection Techniques on Smart Phones","authors":"G. Shanmugasundaram, S. Balaji, T. Mugilan","doi":"10.1109/ICSCAN.2018.8541197","DOIUrl":null,"url":null,"abstract":"Smartphones are rapidly becoming a necessity in our life’s and Android is one of the most popular operating system. Android operating system is widespread in today’s smart phone market due to its open source model, its easy functionality and huge number of apps. There is a tendency of app user to trust on Android OS is for securing the data but it has been proved that Android OS is more vulnerable. Malware detection for Android OS has becoming an upcoming research problem of interest. The objective of this article is to investigate about the various attributes involved in malware detection. Further it explores about the malware detection techniques. Existing detection mechanism uses algorithms such as Naïve bayes algorithm, Bayesian algorithm, Hybrid algorithm, Ada grad algorithm and other machine learning algorithms to train the sets and to detect the malware This article concludes with challenges which are not yet addressed.","PeriodicalId":378798,"journal":{"name":"2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on System, Computation, Automation and Networking (ICSCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN.2018.8541197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Smartphones are rapidly becoming a necessity in our life’s and Android is one of the most popular operating system. Android operating system is widespread in today’s smart phone market due to its open source model, its easy functionality and huge number of apps. There is a tendency of app user to trust on Android OS is for securing the data but it has been proved that Android OS is more vulnerable. Malware detection for Android OS has becoming an upcoming research problem of interest. The objective of this article is to investigate about the various attributes involved in malware detection. Further it explores about the malware detection techniques. Existing detection mechanism uses algorithms such as Naïve bayes algorithm, Bayesian algorithm, Hybrid algorithm, Ada grad algorithm and other machine learning algorithms to train the sets and to detect the malware This article concludes with challenges which are not yet addressed.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
智能手机恶意软件检测技术研究
智能手机正迅速成为我们生活中的必需品,安卓是最受欢迎的操作系统之一。由于其开源模式、简单的功能和大量的应用程序,Android操作系统在当今的智能手机市场上非常普遍。应用程序用户倾向于信任Android操作系统是为了保护数据,但事实证明Android操作系统更容易受到攻击。Android操作系统的恶意软件检测已经成为一个即将到来的研究问题。本文的目的是研究恶意软件检测中涉及的各种属性。进一步探讨了恶意软件检测技术。现有的检测机制使用Naïve贝叶斯算法、贝叶斯算法、混合算法、Ada梯度算法等机器学习算法来训练集合并检测恶意软件。本文总结了尚未解决的挑战。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Improvised Algorithm For Computer Vision Based Cashew Grading System Using Deep CNN Fuzzy Based Active Filter For Power Quality Mitigation Access Level Privacy Protection for Security ANALYSING TWO DIMENSIONAL PROGRESSION OF CRACKS IN BUILDINGS USING SOFTWARE A Survey report of the firefighters on fire hazards of PV fire
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1