With the rapid development of computer network,the society has entered the information and digital era,it plays an important role in speeding up the pace of social development and providing more convenient services fo...With the rapid development of computer network,the society has entered the information and digital era,it plays an important role in speeding up the pace of social development and providing more convenient services for people.However, the security problem of computer network is becoming more and more serious. All kinds of network viruses pose a great threat to the security of computer network.As the most advanced data processing technology currently, data mining technology can effectively resist the invasion of network virus to computer system,and plays an important role in improving the security of the computer network.This paper starts with the concept of data mining technology and the characteristics of computer network virus,and makes an in-depth analysis on the specific application of data mining technology in the computer network virus defense.展开更多
Most epidemic models for the spread of diseases in contact networks take the assumption of the infected probability of a susceptible agent dependent on its absolute number of infectious neighbours. We introduce a new ...Most epidemic models for the spread of diseases in contact networks take the assumption of the infected probability of a susceptible agent dependent on its absolute number of infectious neighbours. We introduce a new epidemic model in which the infected probability of a susceptible agent in contact networks depends not on its degree but on its exposure level. We find that effective average infection rate ^-λ （i.e., the average number of infections produced by a single contact between infected individuals and susceptible individuals） has an epidemic threshold ^λc = 1, which is related to recovery rate, epidemic mechanisms and topology of contact network. Furthermore, we show the dominating importance of epidemic mechanisms in determining epidemic patterns and discussed the implications of our model for infection control policy.展开更多
利用微分动力系统理论分析计算机单种病毒的传播规律,并提出不考虑时滞的计算机病毒传播(the propagation regularity of network viruses without the latent period,PRNV_NWPL)模型和考虑时滞的计算机病毒传播(the propagation regula...利用微分动力系统理论分析计算机单种病毒的传播规律,并提出不考虑时滞的计算机病毒传播(the propagation regularity of network viruses without the latent period,PRNV_NWPL)模型和考虑时滞的计算机病毒传播(the propagation regularity of network viruses with the latent period,PRNV_WLP)模型,并得到病毒是否最终消除的临界值R0。当R0<1时,得到无病平衡点(计算机病毒不流行),R0>1时,得到地方病平衡点(计算机病毒流行)。由此给出清除计算机病毒的方法,并证明无病平衡点和地方病平衡点的局部渐近稳定性。这些方面与统计方法相比可节省人力、物力。展开更多
The paper establishes two stochastic SIRS models with jumps to describe the spread of network virus by cyber war, terrorism and others. First, adding random perturbations proportionally to each variable, we get the dy...The paper establishes two stochastic SIRS models with jumps to describe the spread of network virus by cyber war, terrorism and others. First, adding random perturbations proportionally to each variable, we get the dynamic properties around the positive equilibrium of the deterministic model and the conditions for persistence and extinction. Second, giving a random disturbance to endemic equilibrium, we get a stochastic system with jumps. By modifying the existing Lyapunov function, we prove the positive solution of the system is stochastically stable.展开更多
文摘With the rapid development of computer network,the society has entered the information and digital era,it plays an important role in speeding up the pace of social development and providing more convenient services for people.However, the security problem of computer network is becoming more and more serious. All kinds of network viruses pose a great threat to the security of computer network.As the most advanced data processing technology currently, data mining technology can effectively resist the invasion of network virus to computer system,and plays an important role in improving the security of the computer network.This paper starts with the concept of data mining technology and the characteristics of computer network virus,and makes an in-depth analysis on the specific application of data mining technology in the computer network virus defense.
基金Supported by the Key Program Projects of the National Natural Science of China under Grant No 70431002, and the National Natural Science Foundation of China under Grant No 10372054.
文摘Most epidemic models for the spread of diseases in contact networks take the assumption of the infected probability of a susceptible agent dependent on its absolute number of infectious neighbours. We introduce a new epidemic model in which the infected probability of a susceptible agent in contact networks depends not on its degree but on its exposure level. We find that effective average infection rate ^-λ （i.e., the average number of infections produced by a single contact between infected individuals and susceptible individuals） has an epidemic threshold ^λc = 1, which is related to recovery rate, epidemic mechanisms and topology of contact network. Furthermore, we show the dominating importance of epidemic mechanisms in determining epidemic patterns and discussed the implications of our model for infection control policy.
文摘利用微分动力系统理论分析计算机单种病毒的传播规律,并提出不考虑时滞的计算机病毒传播(the propagation regularity of network viruses without the latent period,PRNV_NWPL)模型和考虑时滞的计算机病毒传播(the propagation regularity of network viruses with the latent period,PRNV_WLP)模型,并得到病毒是否最终消除的临界值R0。当R0<1时,得到无病平衡点(计算机病毒不流行),R0>1时,得到地方病平衡点(计算机病毒流行)。由此给出清除计算机病毒的方法,并证明无病平衡点和地方病平衡点的局部渐近稳定性。这些方面与统计方法相比可节省人力、物力。
基金partially supported by the Natural Science Foundation of Heilongjiang Province(A201420)Educational Reform Project of Heilongjiang Province(JG2013010482)+1 种基金Foundation of Heilongjiang Province Educational Committee(12541696)the Natural Science Foundation of China(11401136,11301112,11301207,11501148)
文摘The paper establishes two stochastic SIRS models with jumps to describe the spread of network virus by cyber war, terrorism and others. First, adding random perturbations proportionally to each variable, we get the dynamic properties around the positive equilibrium of the deterministic model and the conditions for persistence and extinction. Second, giving a random disturbance to endemic equilibrium, we get a stochastic system with jumps. By modifying the existing Lyapunov function, we prove the positive solution of the system is stochastically stable.
