首页> 外文会议>International Conference on Distributed Computing Systems Workshops >An Empirical Study of Passive 802.11 Device Fingerprinting
【24h】

An Empirical Study of Passive 802.11 Device Fingerprinting

机译:无源802.11设备指纹识别的实证研究

获取原文

摘要

802.11 device fingerprinting is the action of characterizing a target device through its wireless traffic. This results in a signature that may be used for identification, network monitoring or intrusion detection. The fingerprinting method can be active by sending traffic to the target device, or passive by just observing the traffic sent by the target device. Many passive fingerprinting methods rely on the observation of one particular network feature, such as the rate switching behavior or the transmission pattern of probe requests. In this work, we evaluate a set of global wireless network parameters with respect to their ability to identify 802.11 devices. We restrict ourselves to parameters that can be observed passively using a standard wireless card. We evaluate these parameters for two different tests: i) the identification test that returns one single result being the closest match for the target device, and ii) the similarity test that returns a set of devices that are close to the target devices. We find that the network parameters transmission time and frame inter-arrival time perform best in comparison to the other network parameters considered. Finally, we focus on inter-arrival times, the most promising parameter for device identification, and show its dependency from several device characteristics such as the wireless card and driver but also running applications.
机译:802.11设备指纹识别是通过其无线流量表征目标设备的动作。这导致可用于识别,网络监测或入侵检测的签名。可以通过将流量发送到目标设备或通过仅观察目标设备发送的流量来激活指纹识别方法。许多被动指纹识别方法依赖于观察一个特定的网络特征,例如速率切换行为或探测请求的传输模式。在这项工作中,我们在识别802.11设备的能力方面评估一组全局无线网络参数。我们将自己限制为可以使用标准无线卡被动地观察的参数。我们为两个不同的测试评估这些参数:i)返回一个单一结果的识别测试是目标设备最接近的匹配,并且II)返回靠近目标设备的一组设备的相似性测试。我们发现,与所考虑的其他网络参数相比,网络参数传输时间和帧间到达时间最佳。最后,我们专注于到达间隔时间,是设备识别的最有希望的参数,并显示其从多个设备特性(例如无线卡和驱动程序)的依赖性,而且还显示出运行应用程序。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号