Beijing Qihoo Technology Company Limited

Beijing Jiaotong University

Yanhui Wang

Lei Guo

Yong Qin

Man Li

Lijie Li

Hao Shi

Sumei Wang

Limin Jia

Shuai Lin

Lifeng Bi

The invention discloses a method and device for recognizing an IP address of a specified category, a defense method and system, wherein the method for recognizing an IP address of a specified category comprises the following steps: collecting behavior record data of several IP addresses (S); extracting preprocessing data from the collected behavior record data, the extracted preprocessing data comprising at least address information of an IP address and time information of a behavior (S); analyzing the extracted preprocessing data to obtain behavior-time distribution data of a user using the IP address (S); and recognizing an IP address of a specified category at least according to the behavior-time distribution data of a user using the IP address (S). By employing the invention, an IP address of a certain category can be located more accurately locate and the accuracy for recognizing an IP address is improved.

Method and device for recognizing an IP address of a specified category, a defense method and system

The invention discloses a complex network-based high speed train system safety evaluation method. The method includes steps as follows: (1) constructing a network model of a physical structure of a high speed train system, and constructing a functional attribute degree of a node based on the network model; (2) extracting a functional attribute degree, a failure rate and mean time between failures of a component as an input quantity, conducting an SVM training using LIBSVM software; (3) conducting a weighted kNN-SVM judgment: an unclassifiable sample point is judged so as to obtain a safety level of the high speed train system. For a high speed train system having a complicated physical structure and operation conditions, the method can evaluate the degree of influences on system safety when a state of a component in the system changes. The experimental result shows that the algorithm has high accuracy and good practicality.

Complex network-based high speed train system safety evaluation method

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Beijing, China

Yanhui Wang