The invention discloses a method for achieving security data acquisition optimizing in a big data environment on the basis of characteristic value feedback. The method comprises the steps that acquired network traffic data is mirrored into two parts, one part is stored off line, and the other part is subjected to real-time analysis; the network traffic data stored off line is subjected to securitycharacteristic analysis, and an obtained security characteristic value is stored in a security characteristic library; during real-time analysis, the network traffic data is filtered according to thesecurity characteristic value, if the network traffic data is matched with the security characteristic value, the network traffic data is security data, and the security data is subjected to real-time analysis. According to the method, the security characteristic value is extracted by means of machine learning, the network traffic data is filtered according to the security characteristic value, the purpose of reducing data, reducing redundant data and improving the real-time analysis efficiency are achieved, and security data acquisition optimizing in the big data environment is achieved.