僵尸跟踪器:在RecDroid中使用聚类方法进行僵尸用户检测

Bahman Rashidi, Carol J. Fung
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引用次数: 6

摘要

RecDroid是一款智能手机权限管理系统,为用户提供细粒度的实时应用权限控制,并根据网络中专家用户的反应,提供是否授予权限的推荐系统。然而,在这样的系统中,恶意软件所有者可能会创建多个bot用户,通过在恶意应用上提供不真实的响应来误导推荐系统。基于阈值的检测方法可以检测到在许多应用上不诚实的恶意用户,但无法检测到针对某些特定应用的恶意用户。在这项工作中,我们提出了一种基于聚类的方法,称为BotTracer,用于寻找由同一主控制的bot用户组,该方法可用于检测具有高声誉分数的bot用户。该方法的关键部分是根据用户的相似度将用户映射到一个图中,并应用聚类算法对用户进行分组。我们使用一组模拟用户的配置文件来评估我们的方法,包括恶意用户和普通用户。实验结果表明,该方法在检测恶意用户方面具有较高的准确性。最后,我们讨论了几个聚类特征及其对聚类结果的影响。
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BotTracer: Bot user detection using clustering method in RecDroid
RecDroid is a smartphone permission management system which provides users with a fine-grained real-time app permission control and a recommendation system regarding whether to grant the permission or not based on expert users' responses in the network. However, in such a system, malware owners may create multiple bot users to misguide the recommendation system by providing untruthful responses on the malicious app. Threshold-based detection method can detect malicious users which are dishonest on many apps, but it cannot detect malicious users that target on some specific apps. In this work, we present a clustering-based method called BotTracer to finding groups of bot users controlled by the same masters, which can be used to detect bot users with high reputation scores. The key part of the proposed method is to map the users into a graph based on their similarity and apply a clustering algorithm to group users together. We evaluate our method using a set of simulated users' profiles, including malicious users and regular ones. Our experimental results demonstrate high accuracy in terms of detecting malicious users. Finally, we discuss several clustering features and their impact on the clustering results.
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