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
Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model ...Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadthfirst traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis(MVA) methods and eliminating interlocking effects.Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.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.
基金supported by the Application Research of the Remote Sensing Technology on Global Energy Internet(JYYKJXM(2017)011)the National Natural Science Foundation of China(61671332,41701518,41771452,41771454,U1736206)+4 种基金National key R&D Project(2016YFE0202300)Hubei Province Technological Innovation Major Project(2017AAA123)Applied Basic Research Program of Wuhan City(2016010101010025)Basic Research Program of Shenzhen(JCYJ20170306171431656)the Fundamental Research Funds for the Central Universities(2042016gf0033)
文摘Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadthfirst traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis(MVA) methods and eliminating interlocking effects.Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.
