The invention relates to an unknown network protocol identification method. The method includes the steps: firstly, taking network data packets as input, and representing each network data packet as a characteristic vector which can be used for classification; secondly, taking the obtained characteristic vectors as input to form a characteristic vector data set, and using a support vector machine oriented active learning method for learning the characteristic vector data set to obtain a classifier aiming at a to-be-tested network protocol; and thirdly, using the obtained classifier to discriminate protocol attributes of to-be-identified network data packets. The invention further provides an unknown network protocol identification system which comprises a data packet modeling module, a classifier construction module and an identification module. The active learning method is adopted, few tagged samples can be used for achieving excellent learning efficiency, and accordingly, the number of the tagged samples in the learning process is reduced effectively, and analyzed network protocols can be identified accurately from miscellaneous network flows.

Unknown network protocol identification method and system

Traffic detection method for peer-to-peer (P2P) network

The invention discloses a method for identifying and predicting nonlinear multivariable key parameters of a circulating fluidized bed boiler, which comprises the following steps of: 1, real-time detection and synchronous transmission of factor signals affecting combustion efficiency of circulating fluidized bed boiler; 2, signal sampling and pretreatment; 3, identification of the nonlinear multivariable key parameters of the circulating fluidized bed boiler; 4 real-time prediction of the nonlinear multivariable key parameters of the circulating fluidized bed boiler; 5, repetition of the step 3 and step 4 to identify all parameters of tested key variables and predict the real-time predicted values of all key parameters of the circulating fluidized bed boiler; and 6, output of results. The method is reasonably designed and convenient to implement; the method can predict the real-time key parameters affecting the stable operation of the circulating fluidized bed boiler with high accuracy, high efficiency, less time and less labor, while making real-time fault diagnosis; therefore, the method is worthy to be used widely.

Method for identifying and predicting nonlinear multivariable key parameters of circulating fluidized bed boiler

The invention discloses a protocol identification method and a protocol identification system, wherein the method comprises the following steps: receiving a data flow of a protocol to be identified, wherein the data flow comprises an uplink data packet and a downlink data packet; splicing the uplink data packet and the downlink data packet and performing format conversion so as to obtain a load data flow, the format of which is converted; and performing protocol identification of the load data flow by adopting a depth learning model so as to obtain a protocol identification result of the data flow for output, wherein the depth learning model is a model obtained by adopting a train data flow in advance and used for identifying a network data flow. The method disclosed by the invention is free from artificial characteristic screening; the protocol identification rate of the network data flow can be increased better; and simultaneously, the cost is reduced.

Protocol identification method and protocol identification system

The invention discloses a network flow application type recognition method. The method comprises the steps that a network data packet is received in real time, a to-be-recognized network data flow isextracted according to the characteristics of the network data packet, and the characteristics of the to-be-recognized network data flow are extracted; and the application type of the to-be-recognizednetwork data flow is recognized according to the characteristics of the to-be-recognized network data flow and a preset application classification model, wherein the application classification modelis obtained through training according to the received characteristics of received network data flows, and the characteristics of the network data flows comprise the data packet length characteristic,the data packet time characteristic and the data packet service type characteristic. The invention further discloses a network flow application type recognition device and a computer readable storagemedium. According to the network flow application type recognition method and device and the computer readable storage medium, by counting and analyzing the behavior characteristics of the network data flow, the network flow application type can be recognized without detecting content of the network data packet, and the method and device are particularly applied to recognition of encrypted network data flows.

Network flow application type recognition method and device and computer readable storage medium

The embodiment of the invention relates to a flow rate identification method and a device thereof. The method comprises the following steps: according to a training algorithm of a support vector machine, training the characteristic vector of a sample of a data packet, and generating a predictive model of the behavior characteristics of the support vector machine; and according to the predicting algorithm of the support vector machine and the predictive model, acquiring the protocol type, to which a communication data stream to be identified belongs. In the embodiment of the invention, all kinds of application layer protocols can be identified accurately, the workload of manual analysis modeling is decreased, the identifying efficiency is improved, the identification process is simple, the problem of invalid behavior characteristic model is reduced, and the anti-interference performance is stronger on network delay and other factors affecting the behavior modes of the data stream.

Flow rate identification method and device thereof

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Flow rate identification method and device thereof