A two-level authentication scheme for clone node detection in smart cities using Internet of things

Clone node attack in IoT sensor devices remains a grave security concern as it paves the way for sinkhole, wormhole, and selective forwarding attacks. In this paper, a two-level authentication scheme named Fingerprint-based Zero-Knowledge Authentication (FZKA) algorithm is proposed to improve the detection rate of clone node among the sensor devices. In the fingerprint generation phase, the base station calculates a distinct fingerprint value for each and every node in the network by gathering neighborhood information, represented in the form of superimposed s-disjunct code matrix. The calculated fingerprint is considered as a secret value and distributed to each cluster nodes for the process of authentication. The FZKA algorithm improves the cloned node detection accuracy with minimal detection time. The simulation results highlight the cloned node detection rate of the proposed scheme by a margin of 92.5% against the existing Exponential Smoothing Algorithm (ETS), Position Verification Method, and Message Verification and Passing algorithms.