如果你能抓住我,就抓住我

Adrian Dabrowski, N. Pianta, Thomas Klepp, M. Mulazzani, E. Weippl
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引用次数: 117

摘要

IMSI捕获器用于移动网络中识别和窃听电话。当供应商数量增加,价格下降时,更多的用户可以使用该设备。基于开源软件的自制设备售价约为1500美元。在本文中,我们识别并描述了检测此类设备在移动网络中产生的伪影的多种方法。我们提出了两个独立的新颖的IMSI Catcher Catcher (ICC)实现,以检测针对每个人隐私的这种威胁。第一种方法采用安装在地理区域内的固定(sICC)测量单元网络,不断扫描所有频段以获取小区公告并对小区网络参数进行指纹识别。这些安装在屋顶上的设备可以覆盖很大的区域。第二种实现是针对标准消费级移动电话(mICC)的应用程序,不需要对它们进行root或越狱。其核心原理是基于地理网络拓扑相关性,促进了当今手机中无处不在的内置GPS接收器和网络蜂窝功能指纹识别技术。后者通过首先学习手机的情况,然后将其与学习到的数据进行匹配,在手机附近工作。我们实施并评估了这两种数字自卫解决方案,并部署了几个固定单元进行长期现场测试。最后,我们描述了如何检测最近发布的拒绝服务攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMSI-catch me if you can: IMSI-catcher-catchers
IMSI Catchers are used in mobile networks to identify and eavesdrop on phones. When, the number of vendors increased and prices dropped, the device became available to much larger audiences. Self-made devices based on open source software are available for about US$ 1,500. In this paper, we identify and describe multiple methods of detecting artifacts in the mobile network produced by such devices. We present two independent novel implementations of an IMSI Catcher Catcher (ICC) to detect this threat against everyone's privacy. The first one employs a network of stationary (sICC) measurement units installed in a geographical area and constantly scanning all frequency bands for cell announcements and fingerprinting the cell network parameters. These rooftop-mounted devices can cover large areas. The second implementation is an app for standard consumer grade mobile phones (mICC), without the need to root or jailbreak them. Its core principle is based upon geographical network topology correlation, facilitating the ubiquitous built-in GPS receiver in today's phones and a network cell capabilities fingerprinting technique. The latter works for the vicinity of the phone by first learning the cell landscape and than matching it against the learned data. We implemented and evaluated both solutions for digital self-defense and deployed several of the stationary units for a long term field-test. Finally, we describe how to detect recently published denial of service attacks.
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