Many real‐world applications, such as smart cities, industrial automation, health care, and so forth, utilize IoT‐enabled devices as a part of wireless networks. IoT devices must have low power and low computation complexity requirements with proper measures of security challenges. Since traditional cryptography techniques are not computationally efficient, other alternatives, such as physical layer key generation (PLKG), is one of the attractive means to achieve security. In this paper, we propose to use a fast independent component analysis (FICA) based KuFaI (Kurtosis and FICA) algorithm for a secured PLKG system. This method reduces data dimensions and improves system performance regarding Bit Disagreement Rate (BDR) and randomness. In KuFaI, we rearrange the received signal strength indicator (RSSI) data set using FICA and then select components based on the kurtosis function. Results demonstrate that the performance of the proposed algorithm is far better than the previously used PCA‐based algorithm.