A Novel Sybil Attack Detection Mechanism for Mobile IoT Networks

IoT (Internet of Things) networks are becoming an integral part of everyday life. The exponential growth in these networks poses various privacy and security threats for the users and the vendors. Among these threats are Sybil attacks, which occurs due to poor authentication capabilities and thus a malicious node gets access to any information on the host. The malicious node uses its' fake identities to impersonate legitimate nodes and transmit misleading data to the central entity. However, conventional cryptographical approaches are not always suitable for IoT nodes due to the their limited resources. Therefore, physical layer security (PLS) solutions become more and more important for IoT networks. In this regard, this study introduces a novel technique for detecting Sybil attacks in mobile networks, which stands in contrast to the current methods developed for stationary environment, i.e., time-invariant channel. Specifically, this work exploits the Doppler shift caused by the mobility in the environment to identify Sybil nodes in the network. If the nodes belong to the same terminal, they experience the same amount of Doppler shift. The detection performance of the proposed scheme has been evaluated under different system configurations. The obtained results show that the performance of the proposed scheme improves as the amount of Doppler shift increases.