As compared to the traditional advertising, word-of-mouth (WOM) communications have striking advantages such as significantly lower cost and much faster propagation, and this is especially the case with the popularity of online social networks. This paper focuses on the modeling and analysis of the WOM marketing. A dynamic model, known as the SIPNS model, capturing the WOM marketing processes with both positive and negative comments is established. On this basis, a measure of the overall profit of a WOM marketing campaign is proposed. The SIPNS model is shown to admit a unique equilibrium, and the equilibrium is determined. The impact of different factors on the equilibrium of the SIPNS model is illuminated through theoretical analysis. Extensive experimental results suggest that the equilibrium is much likely to be globally attracting. Finally, the influence of different factors on the expected overall profit of a WOM marketing campaign is ascertained both theoretically and experimentally. Thereby, some promotion strategies are recommended. To our knowledge, this is the first time the WOM marketing is treated in this way.

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This article addresses the tradeoff between the losses caused by a new virus and the size of the team for developing an antivirus against the virus. First, an individual-level virus spreading model is proposed to capture the spreading process of the virus before the appearance of its natural enemy. On this basis, the tradeoff problem is modeled as a discrete optimization problem. Next, the influences of different factors, including the infection force, the infection function, the available manpower, the alarm threshold, the antivirus development effort and the network topology, on the optimal team size are examined through computer simulations. This work takes the first step toward the tradeoff problem, and the findings are instructive to the decision makers of network security companies.@en

There are plenty of conflicting messages in online social networks. This paper addresses the competition of two conflicting messages. Based on a novel individual-level competing spreading model (the generic UABU model), three criteria for one or two messages to terminate are presented. These criteria manifest the influence of the two message-spreading networks on the evolution of the two messages. Extensive computer simulations show that when a message terminates, the dynamics of a simplified UABU model (the linear UABU model) fits well with the expected evolutionary process of the message. These findings help in understanding the competing spreading process of two conflicting messages.

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To assess the prevalence of disruptive computer viruses in the situation that every node in a network has its own virus-related attributes, a heterogeneous epidemic model is proposed. A criterion for the global stability of the virus-free equilibrium and a criterion for the existence of a unique viral equilibrium are given, respectively. Furthermore, extensive simulation experiments are conducted, and some interesting phenomena are found from the experimental results. On this basis, some policies of suppressing disruptive viruses are recommended.@en

Virus patches can be disseminated rapidly through computer networks and take effect as soon as they have been installed, which significantly enhances their virus-containing capability. This paper aims to theoretically assess the impact of patch forwarding on the prevalence of computer virus. For that purpose, a new malware epidemic model, which takes into full account the influence of patch forwarding, is proposed. The dynamics of the model is revealed. Specifically, besides the permanent susceptible equilibrium, this model may admit an infected or a patched or a mixed equilibrium. Criteria for the global stability of the four equilibria are given, respectively, accompanied with numerical examples. The obtained results show that the spectral radii of the patch-forwarding network and the virus-spreading network both have a marked impact on the prevalence of computer virus. The influence of some key factors on the prevalence of virus is also revealed. Based on these findings, some strategies of containing electronic virus are recommended.

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Alerting at the early stage of malware invasion turns out to be an important complement to malware detection and elimination. This paper addresses the issue of how to dynamically contain the prevalence of malware at a lower cost, provided alerting is feasible. A controlled epidemic model with alert is established, and an optimal control problem based on the epidemic model is formulated. The optimality system for the optimal control problem is derived. The structure of an optimal control for the proposed optimal control problem is characterized under some conditions. Numerical examples show that the cost-efficiency of an optimal control strategy can be enhanced by adjusting the upper and lower bounds on admissible controls.

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There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized meshes (GMs). First, a heuristic growth algorithm (the Proximity- Growth algorithm) is proposed. The resulting proximity-optimal GMs are intuitively robust and hence are adopted as the benchmark. Then, a generalized mesh (GM) is grown up by stepwise optimizing a given measure of network robustness. The following findings are presented: (1) The algebraic connectivity-optimal GMs deviate quickly from the proximity-optimal GMs, yielding a number of less robust GMs. This hints that the rationality of the algebraic connectivity as a measure of network robustness is still in doubt. (2) The effective resistace-optimal GMs and the average edge betweenness-optimal GMs are in line with the proximity-optimal GMs. This partly justifies the two quantities as metrics of network robustness. (3) The efficiency-optimal GMs deviate gradually from the proximity-optimal GMs, yielding some less robust GMs. This suggests the limited utility of the efficiency as a measure of network robustness.

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