NeTS: Medium: HayStack: Fine-grained Visibility and Control of Mobile Traffic for Enhanced Performance, Privacy and Security
NeTS: Medium: HayStack: Fine-grained Visibility and Control of Mobile Traffic for Enhanced Performance, Privacy and Security
批准号:
1564329
负责人:
Narseo Vallina-Rodriguez
金额:
$100.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-08-01 至 2021-08-31
中文摘要
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英文摘要
Despite our growing reliance on mobile phones for a wide range of daily tasks, their operation remains largely opaque even for experts. Mobile users have little insight into how their mobile apps operate and perform in the network, into how (or whether) they protect the information that users entrust to them, and with whom they share user's personal information. A number of previous studies have addressed elements of this problem in a partial fashion, trading off analytic comprehensiveness and deployment scale. This project seeks to overcome the limitations of previous approaches by building a handset-, traffic-, and user-centric mobile measurement platform: the ICSI Haystack. Haystack offers a novel and flexible mobile vantage point capable of correlating real-world mobile traffic with user input and high-fidelity device activity at scale while also enabling mechanisms to aid mobile users to stay in control of their mobile traffic and personal data. The research community, operators and regulatory bodies will also benefit from the novel measurement mechanisms and from the data collected in order to safeguard mobile users and to increase the operational transparency of mobile apps and trackers.To achieve this vision, this project develops novel techniques to perform high-fidelity mobile measurements by capturing user traffic in user-space on the device using native platform support. As a result, Haystack will be available for anyone to install from traditional app stores such as Google Play, thereby enhancing user reach. In order to gain a truly in-depth and broad understanding of the mobile ecosystem, Haystack takes advantage of its local operation to correlate network traffic with user input and local context, such as which app generated a particular network flow and device location, obtained from the operating system itself with real network and user stimuli. Critically, Haystack's system design must be flexible and extensible in order to enable researchers to conduct a wide range of mobile measurements, to cope with new mobile technologies, and to reach a broad cross-section of mobile users. The ability to combine all these features together in user devices makes Haystack an ideal vantage point to conduct a wide range of mobile measurements such as mobile traffic characterization in the wild, privacy leak detection, identifying online tracking services, auditing app security, and network performance measurements.
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