Yurong Song

Nanjing University of Posts and Telecommunications

Influence maximization problem involves selecting a subset of seed nodes within a social network to maximize information spread under a given diffusion model, so how to identify the important nodes is the problem to be considered in this paper. Due to the great differences in the reality of the network, a class of multi-attribute decision fusion me...

The complex dynamics of human mobility, combined with sporadic cases of local outbreaks, make assessing the impact of large-scale social distancing on COVID-19 propagation in China a challenge. In this paper, with the travel big dataset supported by Baidu migration platform, we develop a reactive-diffusion epidemic model on human mobility networks...

Spread velocity, epidemic threshold, and infection density at steady state are three non-negligible features describing the spread of epidemics. Combining these three features together, a new network robustness metric with respect to epidemics was proposed in this paper. The real-time robustness of the network was defined and analyzed. By using the...

The functionalities, such as connectivity and communication capability of complex networks, are related to the number and length of paths between node pairs in the networks. In this paper, we propose a new path connectivity measure by considering the number and length of paths of the network (PCNL) to evaluate network path connectivity. By comparin...

Experimental studies involving control against virus propagation have attracted the interest of scientists. However, most accomplishments have been constrained by the simple assumption of a single virus in various networks, but this assumption apparently conflicts with recent developments in complex network theory, which details that each node migh...

In social networks, the age and the region of individuals are the two most important factors in modeling infectious diseases. In this paper, a spatial susceptible-infected-susceptible (SIS) model is proposed to describe epidemic spreading over a network with region and age by establishing several partial differential equations. Numerical simulation...

With the rapid development of social networks, an increasing number of factors will affect the spread of rumors. In this paper, we simultaneously consider individual activity differences and rumor-refuting nodes, and we propose a new multifactor model that can be used to better analyze the process of rumor spreading in practice. The equilibrium poi...

In the real world, various information can be represented by graph structure data. For example, interpersonal relationships and protein structure. In recent years, with the development of artificial intelligence, graph embedding has become a popular method of network analysis. It can reduce the dimension of network structure data, so that network s...

The robustness of the communication network is an important measurement of network connectivity after some attacks, such as virus and failure. To evaluate the network robustness, many robustness measures have been presented depending on the type of attacks. These measures mainly concentrate on the relation between the robustness of the network and...

Recently it has been recognized that many complex biological, technological and social networks have a multilayer nature and can be described by multilayer networks. Multilayer networks are formed by a set of nodes connected by links having different connotations forming the different layers of the multilayer. Illustrating the centrality of the nod...

Triangle counting is an important step in calculating the network clustering confficient and transitivity, and is widely used in important role recognition, spam detection, community discovery, and biological detection. In this paper, we introduced a GPU-based load balancing triangle counting scheme (GBTCS), which contains three techniques. First,...

In this paper, to avoid chosen-plaintext attacks and to enhance the security, SHA-256 hash value of the plain image is introduced to produce the initial values and parameters of the chaotic system, thus the produced keys and the ciphered image are highly sensitive to changes of the plain image. Based on the plain image related chaotic sequences, a...

Defence against cascading failures is of great theoretical and practical significance. A novel load capacity model with a tunable proportion is proposed. We take degree and clustering coefficient into account to redistribute the loads of broken nodes. The redistribution is local, where the loads of broken nodes are allocated to their nearest neighb...

A large number of real world networks exhibit community structure, and different communities may often possess heterogeneity. In this paper, considering the heterogeneity among communities, we construct a new community network model in which the communities show significant differences in average degree. Based on this heterogeneous community networ...

Multilayer networks are described as complex networks in which each node is related to all other nodes in distinct layers. These layers form a class of cooperating and interacting networks. Examples of such multilayer networks are transport networks, where people can move from one city to another through various modes of transportation. The ranking...

Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves. On the basis of Markov chains theory, a new model characterizing the coupled dynamics between informat...

In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a...

The design of immunization strategies is an extremely important issue for disease or computer virus control and prevention. In this paper, we propose an improved local immunization strategy based on node’s clustering which was seldom considered in the existing immunization strategies. The main aim of the proposed strategy is to iteratively immunize...

Epidemic spreading is closely related with topology of complex networks. Besides heterogeneity in the number of contacts, the clustering of contacts can also have far-reaching epidemiological consequences. Here we investigate the effects of clustering coefficient on epidemic dynamics in complex networks. Results show that the effects of clustering...

Considering the actual behavior of people’s short-term travel, we propose a dynamic small-world community network model with tunable community strength which has constant local links and time varying long-range jumps. Then an epidemic model of susceptible-infected-recovered is established based on the mean-field method to evaluate the inhibitory ef...

The study of rumor spreading has become an important issue on complex social networks. On the basis of prior studies, we propose a modified susceptible–exposed–infected–removed (SEIR) model with hesitating mechanism by considering the attractiveness and fuzziness of the content of rumors. We derive mean-field equations to characterize the dynamics...

A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying me...

The characteristics of wireless sensor networks can be programmed over the air interface lead to a serious threat to its security. This paper proposed susceptible - infectious - recovered model of propagation based on two - dimensional cellular automata, which analyzes the characteristics of dynamic propagation in the wireless sensor networks with...

Adaptive networks are common in real world, describing networks whose links change adaptively with respect to its states, resulting in a dynamical interplay between the state and the topology of the network. Recently, it is demonstrated that the diversity in the interaction intensity is also the crucial feature that reflects the complexity. In fact...

The identifying of influential nodes in large-scale complex networks is an important issue in optimizing network structure and enhancing robustness of a system. To measure the role of nodes, classic methods can help identify influential nodes, but they have some limitations to social networks. Local metric is simple but it can only take into accoun...

In this paper, we propose a novel two-stage rumor spreading Susceptible-Infected-Authoritative-Removed (SIAR) model for complex homogeneous and heterogeneous networks. The interaction Markov chains (IMC) mean-field equations based on the SIAR model are derived to describe the dynamic interaction between the rumors and authoritative information. We...

In this paper, we study epidemic spreading in metapopulation networks wherein each node represents a subpopulation symbolizing a city or an urban area and links connecting nodes correspond to the human traveling routes among cities. Differently from previous studies, we introduce a heterogeneous infection rate to characterize the effect of nodes’ l...

Since many real networks generally have community structures and characteristics of small world, we propose a dynamical small-world network model with strength-tunable community, which can describe the phenomena of local contacts and moving contacts in real life. Then we construct a SIR transmission model on the proposed network on the basis of mea...

In this paper, explicitly considering the influences of an epidemic outbreak on human travel, a time-varying human mobility pattern is introduced to model the time variation of global human travel. The impacts of the pattern on epidemic dynamics in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number o...

Adaptive network is characterized by feedback loop between states of nodes and topology of the network. In this paper, for adaptive epidemic spreading model, epidemic spreading dynamics is studied by using a nonlinear differential dynamic system. The local stability and bifurcation behavior of the equilibrium in this network model are investigated...

In this paper, we study worm dynamics in computer networks composed of many autonomous systems. A novel multi-group SIQR (susceptible-infected-quarantined-removed) model is proposed for computer worms by explicitly considering anti-virus measures and the network infrastructure. Then, the basic reproduction number of worm R0 is derived and the globa...

In the propagation of an epidemic in a population, individuals adaptively adjust their behavior to avoid the risk of an epidemic. Differently from existing studies where new links are established randomly, a local link is established preferentially in this paper. We propose a new preferentially reconnecting edge strategy depending on spatial distan...

A novel scheme to construct a hash function based on a weighted complex dynamical network (WCDN) generated from an original message is proposed in this paper. First, the original message is divided into blocks. Then, each block is divided into components, and the nodes and weighted edges are well defined from these components and their relations. N...

This paper presents a modified susceptible-infected-recovered (SIR) model with the effects of awareness and vaccination to study the epidemic spreading on scale-free networks based on the mean-field theory. In this model, when susceptible individuals receive awareness from their infected neighbor nodes, they will take vaccination measures. The theo...

In this paper, considering the random motion of nodes, we propose an epidemic spreading model on network of mobile environment based on the mean-filed theory. Using the theory of differential dynamical system, the behaviors of epidemic spreading are further analyzed. It is shown that if R 0 ≤ 1, the epidemic always dies out and the disease-free equ...

In this paper, we study the epidemic spreading in scale-free networks and propose a new susceptible-infected-recovered (SIR) model that includes the effect of individual vigilance. In our model, the effective spreading rate is dynamically adjusted with the time evolution at the vigilance period. Using the mean-field theory, an analytical result is...

An adaptive network is a kind of co-evolutionary network in which the behaviors of nodes and the dynamics of the network affect each other. A susceptible-infected-susceptible epidemics spreading model in the adaptive network is proposed using cellular automata. Under different rewriting rules for avoiding the epidemic spreading, the changes in epid...

Network virus propagation is studied for 2D asynchronous cellular automata, and a network virus propagation model with time delay is proposed. The model effectively overwhelms the drawbacks of synchronous automata, and allows researchers to emulate virus propagation in networks on various congestion levels by simply adjusting the factor. It is show...

An adaptive network is a kind of co-evolutionary network in which the behaviors of nodes and the dynamics of the network affect each other. A susceptible-infected-susceptible epidemics spreading model in the adaptive network is proposed using cellular automata. Under different rewriting rules for avoiding the epidemic spreading, the changes in epid...

With considering different anti-attack abilities of nodes and nonuniform transmission of edges in real networks, an SIR model is proposed to investigate the threshold behaviors of epidemic in scale-free networks based on the mean-field theory. In the proposed model, a vulnerability function related to node degree is introduced to describe the diver...

Through investigation of existing immunization strategies in complex networks, a new mobile-node immunization strategy about homogeneous wireless sensor networks is proposed in this paper. The proposed strategy combines with the inherent characteristics of wireless sensor networks. It is shown from simulations that reasonable design of working spee...

This paper proposes a novel approach for fault diagnosis of a time-delay complex dynamical network. Unlike the other methods, assuming that the dynamics of the network can be described by a linear stochastic model, or using the state variables of nodes in the network to design an adaptive observer, it only uses the output variable of the nodes to d...

In this article, a modified susceptible-infected-removed (SIR) model is proposed to study the influence of diversity of node anti-attack abilities on the threshold of propagation in scale-free networks. In particular, a vulnerability function related to node degree is introduced into the model to describe the diversity of a node anti-attack ability...

Considering the nodes with different anti-attack abilities in scale-free networks, we investigated the probabilistic behaviors of malware propagation in scale-free complex networks. Using the cellular automata, we proposed a model of malware propagation in complex networks with the nodes having different anti-attack abilities. In particular, a vuln...

In this paper, based on 1-D cellular automata, the probabilistic behaviors of malware propagation in complex networks are investigated. Neighborhood and state transition functions with integrated expression are established and two models of malware propagation are proposed to evaluate the probabilistic behavior of malware propagation in various net...

In this paper, a novel model of node compromise spreading is proposed to investigate the threat of node compromise spreading in wireless sensor networks. To overcome the disadvantages of random graph model, we investigate node compromise spreading in random geometric graph model constructed according to the parameters of the networks, and compare t...

Based on the inherent characteristics of wireless sensor networks (WSN), the dynamic behavior of malware propagation in flat WSN is analyzed and investigated. A new model is proposed using 2-D cellular automata (CA), which extends the traditional definition of CA and establishes whole transition rules for malware propagation in WSN. Meanwhile, the...

In this paper, based on cellular automata, two models of malware propagation are proposed to evaluate the probabilistic behavior of malware propagation in complex networks. The proposed models can be applied to all kinds of topological networks, such as exponential networks and power law networks and can describe effectively the spatial-temporal pr...

A new kind of discrete probabilistic susceptible-infected model named DP-SI, which can be applied in arbitrary topologies of complex networks, is proposed to investigate the malware propagation and a node information network model is established for investigating complex networks. Based on the proposed models, two major existing immunization strate...

Based on the Chaotic Coupled Map Network (CCMN), a novel scheme for constructing hash functions is proposed in this paper, which transforms messages and establishes a mapping form transformed messages to the parameters of CCMN. Through chaotic iterations, quantization and exclusive-or (XOR) operations, the algorithm can construct hash value with ar...

A model based on cellular automata is proposed to investigate and analyze the process of malware propagation over wireless sensor networks by way of multi-hop broadcast protocols. The model captures the inherent characteristics of wireless sensor networks, i.e. limited resource, channel contention (MAC mechanism), and also reflects the self-organiz...