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Botnets have recently been identified as serious Internet threats that are continually developing and expanding. Identifying botnets in the domain of network security is regarded as a new challenge and topic for research. There are several methods for detecting botnets in networks, and prior research has encountered problems, including a high error and inaccuracy in detection. In this paper, the botnet detection method by using a hybrid of particle swarm optimization (PSO) algorithm with a voting system (BD-PSO-V) was used to improve the challenges of previous studies. The PSO algorithm was employed to select outstanding and effective features in the detection of botnets. The voting system, including a deep neural network algorithm, support vector machine (SVM), and decision tree C4. 5, were utilized to identify botnets and classify samples. The decision-making strategy of the voting system was based on …