In the wireless sensor network infrastructure of smart cities, whether the network traffic is balanced will directly affect the service quality of the network. Because of the traditional WSN (wireless sensor network) architecture, load balancing technology is difficult to meet the requirements of adaptability and high flexibility. This paper proposes a load balancing mechanism based on SDWSN (software defined wireless sensor network). This mechanism utilizes the advantages of a centralized control SDN (software defined network) and flexible traffic scheduling. The OpenFlow protocol is used to monitor the running status and link load information of the network in real time. According to the bandwidth requirement of the data flow, the improved load balanced routing is obtained by an Elman neural network. The simulation results show that the improved SDSNLB (software-defined sensor network load balancing) routing algorithm has better performance than LEACH (Low Energy Adaptive Clustering Hierarchy) protocol in balancing node traffic and improving throughput.

Application programming interface (API) is an excellent feature, since it is a procedure call interface to operation system resource. Behavior features based on API play an important role in analyzing malware variants. However, existing malware detection approaches have a deal of complex operations on construction and matching. Graph matching is an NP-complete problem and is time consuming because of computational complexity. To address these issues, a promising approach is proposed to construct the classified behavior features from different malware families. In the proposed approach, a classified behavior feature consists of a kernel object (an API call parameter) and a series of operations (an API trace). Besides, a classified behavior graph (CBG) is represented as a number by hash to reduce workload and matching time. Subsequently, multiple machine learning classifiers are used for system classification. In particular, to verify the efficiency of our approach, we perform a series of experiments with different families. Experiments on 1220 malware samples show that the true positive rate is up to 88.3% and the false positive rate keeps within 3.9% by Support Vector Machine (SVM).

IP mutation is an effective moving target defense method against sniffer or hijacking attack. The mutation frequency is one of the most important parameters that influence the security of mutation method. However, higher frequency is inconsistent with data transmission that will decrease the efficiency and stability. Moreover, most of existing mutation methods have shortcomings under various conditions, such as address allocation or network architecture. In this paper, sliding window and full transparent (SWIFT) scheme for IPv6 address mutation is proposed. With the sliding window design, the SWIFT scheme can provide an address mutation with very high frequency. This scheme is transparent to both network side and user side so that the existing equipment and architecture need not to be changed. A prototype by the SWIFT scheme is designed and developed over an IPv6 network. The experiment result shows that our method can achieve high transmission efficiency with a high mutation frequency, which provides a good experience for most mutation methods.

Network virtualization has been proposed as a key contribution to the future internetworking paradigm and is expected to play a crucial role in the next generation Internet. Although interesting progress has been made towards network virtualization, end-to-end Quality of Service (QoS) provisioning for multimedia services in network virtualization environments is still an important open topic. In this paper, we tackle this challenging issue by modeling multimedia service delivery in network virtualization and proposing efficient path selection algorithms for virtual networks. The main contributions of this paper are a model for the end-to-end multimedia service delivery in network virtualization environments, proposal of efficient algorithms for selecting paths traversing the network infrastructure for QoS provisioning in virtual networks, and analysis of the effectiveness and efficiency of the proposed algorithms. Both theoretical analysis and experimental results show that the modeling technique and the algorithms proposed in this paper are general and flexible, and therefore applicable to the delivery of multimedia content in various heterogeneous networking systems in the next generation Internet.

Although the frequency of Internet worm's outbreak is decreased, the impact of worm on people's wealth security and society's stabilization is still an unnegligible problem, especially the emergence of botnet. With the growth of variable network structure and applications, such as P2P network, Internet worms can explore more fast and covert ways to propagate. Hence, an accurate worm propagation model is urgently needed. In this paper, the concept and structure of worms are presented, then the typical propagation models in different environment are discussed, and the Advantages and Disadvantages of different models are given. It is our hope that others in the community who need to get up to speed in the worm literature can benefit from this survey.