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Relationship between User Privacy and Application Permissions in Smartphone Platforms

机译:智能手机平台中用户隐私与应用程序许可之间的关系

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摘要

Smartphone devices running mobile operating systems are an integral part of society. Smartphone devices are used every day for communication, work purposes, online banking, shopping, and getting information, etc. There is a perception that smartphones are immune from malware and attacks, but they introduce a lot of potential privacy risks to end-users. Smartphone capabilities that can be misused include access to sensitive information such as the International Mobile Equipment Identity (IMEI) phone identifier, location tracking, and Short Message Service (SMS) privileges, which may cost the user money.;This research presents a systematic study, which identifies potential attacks and threats, and introduces a new detection method that uses machine learning models to classify apps into safe, benign, and malicious categories. The goal is to explore and quantify the relationship between app permissions and user privacy. This research would also provide a novel method to measure the severity of user privacy violation.;Previous work in malicious app detection considered just one or two features, such as the category to which each app belongs and if there are more app permissions than required, but they never considered the impact of app permissions on smartphone malware and ad networks. Also, a lot of research has been conducted on identifying if there is information leakage that apps can conduct, but to the best of my knowledge there is not a formal method to measure user privacy violation. It occurs when the user is not notified about the resources or information accessed and if the information is misused when stored in third-party servers.;The present research addresses these issues. In addition, this study develops the Android Application Permission Manager (AAPM) privacy app which would inform users about (1) over-privileged app permissions, (2) the number of ad networks associated with each app, (3) potential privacy threats that each app permission can expose the user to, and (4) how to provide a balance between app functionality and protection of the user privacy.
机译:运行移动操作系统的智能手机设备是社会不可或缺的一部分。智能手机设备每天都用于通讯,工作,网上银行,购物和获取信息等。人们普遍认为,智能手机可以抵御恶意软件和攻击,但会给最终用户带来很多潜在的隐私风险。可被滥用的智能手机功能包括访问敏感信息,例如国际移动设备身份(IMEI)电话标识符,位置跟踪和短消息服务(SMS)特权,这可能会浪费用户金钱。 ,它可以识别潜在的攻击和威胁,并引入了一种新的检测方法,该方法使用机器学习模型将应用分为安全,良性和恶意类别。目的是探索和量化应用权限和用户隐私之间的关系。这项研究还将提供一种新颖的方法来衡量侵犯用户隐私的严重性。;恶意应用程序检测的先前工作仅考虑了一个或两个功能,例如每个应用程序所属的类别以及是否有超过所需权限的应用程序权限,但他们从未考虑过应用权限对智能手机恶意软件和广告网络的影响。此外,已经进行了很多研究来确定应用程序是否可以进行信息泄漏,但是据我所知,还没有一种正式的方法来衡量用户隐私侵害。当未通知用户有关所访问的资源或信息的信息以及存储在第三方服务器中的信息被滥用时,就会发生这种情况。本研究解决了这些问题。此外,本研究还开发了Android应用程序权限管理器(AAPM)隐私应用程序,该应用程序将通知用户以下信息:(1)特权过高的应用程序权限;(2)与每个应用程序关联的广告网络的数量;(3)潜在的隐私威胁每个应用程序权限都可以使用户接触到(4)如何在应用程序功能和保护用户隐私之间取得平衡。

著录项

  • 作者

    Caushaj, Eralda.;

  • 作者单位

    Oakland University.;

  • 授予单位 Oakland University.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 159 p.
  • 总页数 159
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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