I Know Your Social Network Accounts: A Novel Attack Architecture for Device-Identity Association
I Know Your Social Network Accounts: A Novel Attack Architecture for Device-Identity Association
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DOI：
10.1109/tdsc.2022.3147785
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发表时间：
2023-03
影响因子：
7.3
通讯作者：
Yinhao Xiao;Yizhen Jia;Xiuzhen Cheng;Shengling Wang;Jian Mao;Zhenkai Liang
中科院分区：
文献类型：
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作者：
Yinhao Xiao;Yizhen Jia;Xiuzhen Cheng;Shengling Wang;Jian Mao;Zhenkai Liang
在线社交网络彻底改变了人们相互交流的方式。当各种社交网络信息随时间聚集时，形成用户的丰富在线简档。由于由移动的设备提供的各种特征，用户的在线社交活动被紧密地绑定到他的电话，并且方便地（有时不必要地）可用于社交网络。在这篇文章中，我们提出了一种新的攻击架构，表明攻击者可以推断用户的社交网络身份背后的移动终端通过新的维度。具体来说，我们首先开发了用户的设备系统状态和社交网络事件之间的关联，该关联利用了基于学习的记忆回归模型等多种机制来推断用户在社交网络应用中的可能账户。然后，我们利用社交网络到社交网络的关联，通过该关联，我们将不同社交网络之间的信息关联起来，以识别目标用户的帐户。我们在三个流行的社交网络上实现并评估了这些攻击，结果证实了我们设计的有效性。
Online social networks revolutionize the way people interact with each other. When various social network information aggregates over time, a rich online profile of the user is formed. Owing to the various features provided by mobile devices, a user's online social activities are tightly tied to his phone, and are conveniently, sometimes unnecessarily, available to social networks. In this article, we propose a novel attack architecture to show that attackers can infer a user's social network identities behind a mobile device through new dimensions. Specifically, we first developed a correlation between a user's device system states and the social network events, which leverage multiple mechanisms such as the learning-based memory regression model, to infer the possible accounts of the user in the social network app. Then we exploited the social network to social network correlation, via which we correlated information across different social networks, to identify the accounts of the target user. We implemented and evaluated these attacks on three popular social networks, and the results corroborate the effectiveness of our design.