Trust Evaluation in Mobile Devices: An Empirical Study

Richard S. Weiss, L. Reznik, Yanyan Zhuang, Andrew Hoffman, Darrel Pollard, Albert Rafetseder, Tao Li, Justin Cappos
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引用次数: 8

Abstract

Mobile devices today, such as smartphones and tablets, have become both more complex and diverse. This paper presents a framework to evaluate the trustworthiness of the individual components in a mobile system, as well as the entire system. The major components are applications, devices and networks of devices. Given this diversity and multiple levels of a mobile system, we develop a hierarchical trust evaluation methodology, which enables the combination of trust metrics and allows us to verify the trust metric for each component based on the trust metrics for others. The paper first demonstrates this idea for individual applications and Android-based smartphones. The methodology involves two stages: initial trust evaluation and trust verification. In the first stage, an expert rule system is used to produce trust metrics at the lowest level of the hierarchy. In the second stage, the trust metrics are verified by comparing data from components and a trust evaluation is produced for the combined system. This paper presents the results of two empirical studies, in which this methodology is applied and tested. The first study involves monitoring resource utilization and evaluating trust based on resource consumption patterns. We measured battery voltage, CPU utilization and network communication for individual apps and detected anomalous behavior that could be indicative of malicious code. The second study involves verification of the trust evaluation by comparing the data from two different devices: the GPS location from an Android smartphone in an automobile and the data from an on-board diagnostics (OBD) sensor of the same vehicle.
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移动设备信任评价的实证研究
如今的移动设备,如智能手机和平板电脑,已经变得更加复杂和多样化。本文提出了一个评估移动系统中各个组件以及整个系统可信度的框架。其主要组成部分是应用程序、设备和设备网络。考虑到移动系统的多样性和多层次,我们开发了一种分层信任评估方法,该方法可以组合信任指标,并允许我们根据其他组件的信任指标验证每个组件的信任指标。这篇论文首先为个人应用程序和基于android的智能手机展示了这个想法。该方法包括初始信任评估和信任验证两个阶段。在第一阶段,使用专家规则系统在层次结构的最低级别生成信任度量。在第二阶段,通过比较来自组件的数据来验证信任度量,并为组合系统生成信任评估。本文介绍了两项实证研究的结果,并对该方法进行了应用和检验。第一项研究涉及基于资源消耗模式的资源利用监测和信任评价。我们测量了单个应用程序的电池电压、CPU利用率和网络通信,并检测到可能指示恶意代码的异常行为。第二项研究涉及通过比较来自两个不同设备的数据来验证信任评估:来自汽车中的Android智能手机的GPS位置和来自同一辆汽车的车载诊断(OBD)传感器的数据。
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