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The main research direction of hardware trojan detection is based on the side channel analysis. This paper proposes an optimized support vector machine(SVM) classification method to improve the accuracy and speed when analyzing the data for detection hardware trojan. Firstly, the principal component analysis is used for data dimension reduction. Then, genetic algorithm is used to accelerate the selection of optimal penalty coefficient and kernel function parameters. Finally, the hardware trojan detection classifier is built with SVM. Experimental results show that the optimized SVM method improves the detection speed and accuracy, and can effectively detect hardware trojans with the area of 0.1%,the accuracy can be increased by 15.6%，and the time consumption can be reduced by 98.1%.