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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Weiss, R. Reznik, L. Yanyan Zhuang Hoffman, A. Pollard, D. Rafetseder, A. Tao Li Cappos, J. |
| Copyright Year | 2015 |
| Description | Author affiliation: Evergreen State Coll., Olympia, WA, USA (Weiss, R.) || Comput. Sci. & Eng., New York Univ., New York, NY, USA (Yanyan Zhuang; Rafetseder, A.; Tao Li; Cappos, J.) || Dept. of Comput. Sci., Rochester Inst. of Technol., Rochester, NY, USA (Reznik, L.; Hoffman, A.; Pollard, D.) |
| 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. |
| Starting Page | 25 |
| Ending Page | 32 |
| File Size | 580740 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781467379526 |
| DOI | 10.1109/Trustcom.2015.353 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-20 |
| Publisher Place | Finland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Computer science Privacy Trust metrics Electronic mail Security Smart phones Mobile computing |
| Content Type | Text |
| Resource Type | Article |
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