演示:AntMonitor:一个移动流量监控和实时防止隐私泄露的系统

A. Shuba, Anh Le, Minas Gjoka, Janus Varmarken, Simon Langhoff, A. Markopoulou
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引用次数: 9

摘要

移动设备在当今的互联网中扮演着至关重要的角色,人们对使用它们作为从边缘进行网络测量的有利位置越来越感兴趣。与此同时,这些设备存储着个人敏感信息,越来越多的应用程序泄露了这些信息。我们提出AntMonitor——这是同类系统中第一个支持(i)以尊重用户隐私偏好的方式收集大规模、语义丰富的网络流量和(ii)实时检测和防止私人信息泄露的系统。第一个特性使AntMonitor成为想要收集和分析大规模但细粒度移动测量的网络研究人员的强大工具。第二个属性可以作为使用AntMonitor并为分析提供数据的激励。作为概念验证,我们开发了一个AntMonitor的原型,对9个用户进行了2个月的监控,并从151个应用程序中收集和分析了20gb的移动数据。初步结果表明,从AntMonitor收集的细粒度数据可以使应用程序分类比最先进的方法具有更高的准确性。此外,我们还演示了AntMonitor可以帮助防止几个应用程序通过未加密的流量泄露私人信息,包括电话号码、电子邮件和设备标识符。
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Demo: AntMonitor: A System for Mobile Traffic Monitoring and Real-Time Prevention of Privacy Leaks
Mobile devices play an essential role in the Internet today, and there is an increasing interest in using them as a vantage point for network measurement from the edge. At the same time, these devices store personal, sensitive information, and there is a growing number of applications that leak it. We propose AntMonitor-- the first system of its kind that supports (i) collection of large-scale, semantic-rich network traffic in a way that respects users' privacy preferences and (ii) detection and prevention of leakage of private information in real time. The first property makes AntMonitor a powerful tool for network researchers who want to collect and analyze large-scale yet fine-grained mobile measurements. The second property can work as an incentive for using AntMonitor and contributing data for analysis. As a proof-of-concept, we have developed a prototype of AntMonitor, deployed it to monitor 9 users for 2 months, and collected and analyzed 20 GB of mobile data from 151 applications. Preliminary results show that fine-grained data collected from AntMonitor could enable application classification with higher accuracy than state-of-the-art approaches. In addition, we demonstrated that AntMonitor could help prevent several apps from leaking private information over unencrypted traffic, including phone numbers, emails, and device identifiers.
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