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Guided socialbots: Infiltrating the social networks of specific organizations' employees

机译：引导型社交机器人：渗透到特定组织员工的社交网络

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摘要

A dimension of the Internet that has gained great popularity in recent years is the platform of online social networks (OSNs). Users all over the world write, share, and publish personal information about themselves, their friends, and their workplaces within this platform of communication. In this study we demonstrate the relative ease of creating malicious socialbots that act as social network "friends", resulting in OSN users unknowingly exposing potentially harmful information about themselves and their places of employment. We present an algorithm for infiltrating specific OSN users who are employees of targeted organizations, using the topologies of organizational social networks and utilizing socialbots to gain access to these networks. We focus on two well-known OSNs - Facebook and Xing - to evaluate our suggested method for infiltrating key-role employees in targeted organizations. The results obtained demonstrate how adversaries can infiltrate social networks to gain access to valuable, private information regarding employees and their organizations.
机译：在线社交网络（OSN）平台是近年来获得广泛普及的Internet维度。世界各地的用户在此通信平台中编写，共享和发布有关自己，朋友和工作场所的个人信息。在这项研究中，我们证明了创建充当社交网络“朋友”的恶意社交机器人相对容易，从而导致OSN用户在不知不觉中暴露出有关自己及其工作地点的潜在有害信息。我们提出了一种用于渗透特定OSN用户的算法，这些OSN用户是目标组织的雇员，使用组织社交网络的拓扑结构并利用socialbots来访问这些网络。我们专注于两个著名的OSN（Facebook和Xing），以评估我们建议的渗透目标组织中关键角色员工的方法。获得的结果表明，对手如何渗透到社交网络中，以获取有关员工及其组织的宝贵私人信息。

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