Nowadays, online social networks have become an essential part of humans. However, there are some dark side to this widespread use of online social networks. One of them is the fact that many attackers have succeeded to clone celebrities’ profiles and have attracted hundreds or thousands of followers. This type of forging has caused many problems for famous people. This phenomenon is commonly known as Identity Cloning Attack which is abbreviated to ICA in the literature. ICA occurs when a malicious user selects one of the famous users of a social network as his victim. The attacker then creates a user account similar to the victim’s profile and embarks on various malicious social activities. In this paper, we have proposed an automatic method to identify cloned profiles. This method consists of three main steps and is implemented on Hadoop framework using the MapReduce programming model. In the first step, we count the number of followers of each user and store it as an attribute for their profile. In the second step, the network users are clustered based on their profile attributes and their number of followers. Subsequently, we move all the profiles within the same cluster as the victim’s profile to the next step and consider them as suspicious profiles. The victim’s profile is a profile of a celebrity, where the proposed method is conducted to verify its authenticity. In the third step, we eventually select the profile with the highest rank as the valid profile. This method of ranking the profiles is based on the outcome of PageRank algorithm in the first step. This method is easily applicable and does not require any additional information for identifying the original user account. Furthermore, this method employs a distributed processing framework, limits the search space, and decreases the required computation by clustering the profiles. We have applied the suggested method to a dataset that we collected from Instagram. Our findings were quite promising, and in some situations, we were able to identify all the cloned profiles with a 100% accuracy. The results are comparable to the best ones in this area of study.

中文翻译：

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使用PageRank在在线社交网络中自动进行ICA检测

如今，在线社交网络已成为人类不可或缺的一部分。但是，这种在线社交网络的广泛使用存在一些弊端。其中一个事实是，许多攻击者成功克隆了名人的个人资料，并吸引了成千上万的追随者。这种锻造给名人造成了许多问题。这种现象通常称为身份克隆攻击，在文献中简称为ICA。当恶意用户选择某个社交网络的知名用户之一作为其受害者时，就会发生ICA。然后，攻击者创建一个类似于受害者个人资料的用户帐户，并着手进行各种恶意社交活动。在本文中，我们提出了一种自动方法来识别克隆的配置文件。该方法包括三个主要步骤，并使用MapReduce编程模型在Hadoop框架上实现。第一步，我们计算每个用户的关注者数量，并将其存储为他们的个人资料的属性。第二步，根据网络用户的个人资料属性和关注者数量对网络用户进行聚类。随后，我们将与受害人档案相同的群集中的所有档案移到下一步，并将其视为可疑档案。受害者的个人资料是名人的个人资料，在此进行建议的方法以验证其真实性。第三步，我们最终选择排名最高的配置文件作为有效配置文件。这种对档案进行排名的方法是基于第一步中PageRank算法的结果。此方法很容易应用，不需要任何其他信息即可标识原始用户帐户。此外，该方法采用分布式处理框架，限制了搜索空间，并通过对配置文件进行聚类来减少所需的计算。我们已将建议的方法应用于从Instagram收集的数据集。我们的发现很有前途，在某些情况下，我们能够以100％的准确性识别所有克隆的谱。结果与该研究领域的最佳结果相当。我们已将建议的方法应用于从Instagram收集的数据集。我们的发现很有前途，在某些情况下，我们能够以100％的准确性识别所有克隆的谱。结果与该研究领域的最佳结果相当。我们已将建议的方法应用于从Instagram收集的数据集。我们的发现很有前途，在某些情况下，我们能够以100％的准确性识别所有克隆的谱。结果与该研究领域的最佳结果相当。