The evolution of the Internet of Things (IoT) has increased the connection of personal devices, mainly taking into account the habits and behavior of their owners. These environments demand access control mechanisms to protect them against intruders, like Sybil attacks. that can compromise data privacy or disrupt the network operation. The Social IoT paradigm enables access control systems to aggregate community context and sociability information from devices to enhance robustness and security. This work introduces the ELECTRON mechanism to control access in IoT networks based on social trust between devices to protect the network from Sybil attackers. ELECTRON groups IoT devices into communities by their social similarity and evaluates their social trust, strengthening the reliability between legitimate devices and their resilience against the interaction of Sybil attackers. NS-3 Simulations show the ELECTRON performance under Sybil attacks on several IoT communities so that it has gotten to detect more than 90% of attackers in a scenario with 150 nodes into offices, schools, gyms, and~parks communities, and in other scenarios for same communities it achieved around of 90\% of detection. Furthermore, it provided high accuracy, over 90-95%, and false positive rates closer to zero.

中文翻译：

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基于网络社区感知和社会信任的物联网访问控制对抗女巫攻击

物联网 (IoT) 的发展增加了个人设备的连接，主要是考虑到其所有者的习惯和行为。这些环境需要访问控制机制来保护它们免受入侵者的侵害，例如 Sybil 攻击。这可能会损害数据隐私或破坏网络运行。社交物联网范式使访问控制系统能够聚合来自设备的社区背景和社交信息，以增强稳健性和安全性。这项工作引入了 ELECTRON 机制，以基于设备之间的社会信任来控制物联网网络中的访问，以保护网络免受女巫攻击者的攻击。ELECTRON 根据物联网设备的社会相似性将它们分组到社区中，并评估它们的社会信任度，加强合法设备之间的可靠性及其抵御 Sybil 攻击者交互的能力。NS-3 模拟显示了在 Sybil 攻击下对多个 IoT 社区的 ELECTRON 性能，因此在办公室、学校、体育馆和公园社区等 150 个节点的场景中，它已经能够检测到 90% 以上的攻击者对于相同的社区，它实现了大约 90% 的检测。此外，它提供了超过 90-95% 的高精度和接近于零的误报率。在相同社区的其他场景中，它实现了大约 90% 的检测。此外，它提供了超过 90-95% 的高精度和接近于零的误报率。在相同社区的其他场景中，它实现了大约 90% 的检测。此外，它提供了超过 90-95% 的高精度和接近于零的误报率。