A novel attack to track users based on the behavior patterns
A novel attack to track users based on the behavior patterns
复制标题
一种基于行为模式跟踪用户的新颖攻击
DOI：
10.1002/cpe.3891
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发表时间：
2017
影响因子：
2
通讯作者：
Luo Junzhou
中科院分区：
文献类型：
--
作者：
Gu Xiaodan;Yang Ming;Shi Congcong;Ling Zhen;Luo Junzhou
目前，世界各地的人们每天都使用互联网来访问各种服务，例如电子邮件和在线购物。然而，基于行为的跟踪攻击对用户的隐私构成了相当大的威胁。依靠互联网活动中的特征模式，这种攻击可以链接用户的多个会话。在本文中，我们研究了基于行为的跟踪攻击，并提出了一些减轻威胁的对策。我们对原始流量数据进行预处理，然后提取从较低层网络数据包到高层应用程序相关流量的特征。具体来说，我们关注四种类型的应用程序级流量来推断用户的习惯，包括 HTTP、IM、电子邮件和 P2P。此外，我们提取输入购物网站的网络查询并对它们进行分类以推断用户的偏好。然后，我们构建了偏好模型并提出了一种改进方法。为了进行评估，我们收集现实环境中的流量以构建大规模数据集。根据用户活跃度选出509个用户。当使用词频-逆文档频率变换时，改进的方法平均可以正确识别93.79%的实例。我们广泛的实证实验证明了我们方法的有效性和效率。最后，我们讨论并评估了几种对策。版权所有 © 2016 约翰·威利父子有限公司
Currently, people around the world daily use the Internet to access various services, such as e‐mail and online shopping. However, the behavior‐based tracking attacks have posed a considerable threat to users' privacy. Relying on characteristic patterns within the Internet activities, this attack can link a user's multiple sessions. In this paper, we investigate the behavior‐based tracking attack and propose some countermeasures to mitigate the threat. We preprocess the raw traffic data and then extract features ranging from lower layer network packets to high‐level application‐related traffic. Specifically, we focus on four types of application‐level traffic to infer users' habits, including HTTP, IM, e‐mail, and P2P. In addition, we extract the web queries entered into shopping websites and classify them to infer users' preferences. Then, we construct the preference models and propose an improved method. For evaluation, we collect traffic in the real‐world environment to construct a large‐scale dataset. Five hundred and nine users are selected in terms of the user's active degree. When the term frequency–inverse document frequency transformation is used, the improved method can identify an average of 93.79% instances correctly. Our extensive empirical experiments demonstrate the effectiveness and efficiency of our approaches. Finally, we discuss and evaluate several countermeasures. Copyright © 2016 John Wiley & Sons, Ltd.