Haystack: A Multi-Purpose Mobile Vantage Point in User Space
arXiv:1510.01419
Abstract
Despite our growing reliance on mobile phones for a wide range of daily tasks, their operation remains largely opaque. A number of previous studies have addressed elements of this problem in a partial fashion, trading off analytic comprehensiveness and deployment scale. We overcome the barriers to large-scale deployment (e.g., requiring rooted devices) and comprehensiveness of previous efforts by taking a novel approach that leverages the VPN API on mobile devices to design Haystack, an in-situ mobile measurement platform that operates exclusively on the device, providing full access to the device's network traffic and local context without requiring root access. We present the design of Haystack and its implementation in an Android app that we deploy via standard distribution channels. Using data collected from 450 users of the app, we exemplify the advantages of Haystack over the state of the art and demonstrate its seamless experience even under demanding conditions. We also demonstrate its utility to users and researchers in characterizing mobile traffic and privacy risks.
13 pages incl. figures
References in corpus (1)
Cited by in corpus (7)
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- AntShield: On-Device Detection of Personal Information Exposure
- An Analysis of Pre-installed Android Software
- Exposures Exposed: A Measurement and User Study to Assess Mobile Data Privacy in Context