As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenien...As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.展开更多
Scoring in a basketball game is a highly dynamic, non-linear process. NBA teams try to be more and more competitive each season. For instance, they incorporate into their rosters the best players in the world. This an...Scoring in a basketball game is a highly dynamic, non-linear process. NBA teams try to be more and more competitive each season. For instance, they incorporate into their rosters the best players in the world. This and other mechanisms concur to make the scoring process in NBA games exciting and rarely predictable. This paper is to study the behavior of timing and scoring in basketball gaines. The authors analyze all the games in five NBA regular seasons （2005-06, 2006-07, 2007-08, 2008-09, 2009-10）, for a total of 6150 games. Scoring does not behave uniformly; therefore, the authors also analyze the distributions of the differences in points in the basketball games. To further analyze the behavior of the tail of the distribution, the authors also carry out a semilog-plot and a log-log plot to verify whether this trend approaches a Poisson distribution or a PL. This paper reveals different areas of behavior related to the score, with specific instances of time that could be considered tipping points of the game. The presence of these critical points suggests that there are phase transitions where the dynamic scoring of the games varies significantly.展开更多
基金supported by the National Science Key Lab Fund under Grant No. KJ-15-104the Project of Henan Provincial Key Scientific and Technological Research under Grant No. 132102210003
文摘As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.
文摘Scoring in a basketball game is a highly dynamic, non-linear process. NBA teams try to be more and more competitive each season. For instance, they incorporate into their rosters the best players in the world. This and other mechanisms concur to make the scoring process in NBA games exciting and rarely predictable. This paper is to study the behavior of timing and scoring in basketball gaines. The authors analyze all the games in five NBA regular seasons （2005-06, 2006-07, 2007-08, 2008-09, 2009-10）, for a total of 6150 games. Scoring does not behave uniformly; therefore, the authors also analyze the distributions of the differences in points in the basketball games. To further analyze the behavior of the tail of the distribution, the authors also carry out a semilog-plot and a log-log plot to verify whether this trend approaches a Poisson distribution or a PL. This paper reveals different areas of behavior related to the score, with specific instances of time that could be considered tipping points of the game. The presence of these critical points suggests that there are phase transitions where the dynamic scoring of the games varies significantly.
