Fangwei Wang

Stability analysis of a SEIQV epidemic model for rapid spreading worms

Internet worms have drawn significant attention owing to their enormous threats to the Internet. Due to the rapid spreading nature of Internet worms, it is necessary to implement automatic mitigation on the Internet. Inspired by worm vaccinations, we propose a novel epidemic model which combines both vaccinations and dynamic quarantine methods, referred to as SEIQV model. Using SEIQV model, we obtain the basic reproduction number that governs whether or not a worm is extinct. The impact of different parameters on this model is studied. Simulation results show that the performance of our model is significantly better than other models, in terms of decreasing the number of infected hosts and reducing the worm propagation speed.

A Worm Defending Model with Partial Immunization and Its Stability Analysis

Internet worms, a great threat to the Internet infrastructure, can propagate horrendously through networks, and reduce network security and cause economic losses. In order to effectively defend against worms, this paper proposes a novel epidemic SVEIR model with partial immunization. In the SVEIR model, we obtain the basic reproduction number for determining whether the worm dies out completely. The global stabilities of infection-free equilibrium and endemic equilibrium are proven using a Lyapunov function and a geometrical approach. The impact of different parameters of this model is studied. Simulation results show that the number of susceptible and infected hosts is consistent with theoretical analysis. The model provides a theoretical foundation for control and forecasting Internet worms. Index Terms—Network security, Internet worm, stability analysis, endemic equilibrium, partial immunization

Modelling and Analyzing Passive Worms over Unstructured Peer-to-Peer Networks

Passive worm have posed serious security threats to the functioning of unstructured P2P networks. A delayed SEIRS epidemic model with death, off line and online rate is constructed based on the actual situation of P2P users. The basic reproduction number that governs whether a passive worm is extinct or not is obtained. In this model, time delay consists of latent and temporary immunity periods. The impact of different parameters on this model is studied with simulation results, especially the effect of time delay, which can provide an important guideline in the control of unstructured P2P networks as well as passive worm defense.

Stability Analysis of a Worm Propagation Model with Quarantine and Vaccination

Internet worms pose a serious threat to the Internet security. In order to effectively defend against Internet worms, this paper proposes a novel epidemic ＂e-SEIQV＂ model with quarantine and vaccination. Using this ＂e-SEIQV＂ model, we obtain the basic reproduction number for deter- mining whether the worm dies out completely. The global stability of the worm-free equilibrium and the local stability of endemic equilibrium are proved, and determined by the basic reproduction number. Besides the impact of different parameters of this model is studied. Simulation results show that the number of susceptible and infected hosts are consistent with the theoretical analysis. The model provides a theoretical foundation for controlling and forecasting Internet worms.

An SVEIR Defending Model with Partial Immunization for Worms

Internet worms can propagate across networks horrendously, reduce network security remarkably, and cause economic losses heavily. How to quickly eliminate the Internet worms using partial immunization becomes a big issue for sustaining Internet infrastructure smoothly. This paper addresses this issue by presenting a novel worm attack model through incorporating a saturated incidence rate and a partial immunization rate, named SVEIR model. Using the basic reproduction number, we derive the global stability of the infection-free equilibrium and local stability of the unique endemic equilibrium. Numerical methods are employed to solve and simulate the developed system and also verify the proposed SVEIR model. Simulation results show that the partial immunization is highly effective for eliminating worms.

Stability Analysis of a Rapid Scanning Worm Propagation Model with Quarantine Strategy

Rapid scanning worms are a great threat to Internet infrastructure. To effectively defend against them, this paper proposed an epidemic SEIQV model with quarantine and vaccination strategies. Through analysis of this model, its stability condition is obtained: When the basic reproduction number is less than or equal to one, our model is stable at its worm-free equilibrium where worms finally get eliminated. Simulation results show that quarantine strategy is efficient, in terms of the number of infected hosts and reducing worm propagation speed.

Combating self-learning worms by using predators

Internet worms increasingly threaten the Internet hosts and services. More terribly, good point set scanning-based self-learning worms can reach a stupendous propagation speed in virtue of the non-uniform vulnerable-host distribution. In order to combat self-learning worms, this paper proposes an interaction model. Using the interaction model, we obtain the basic reproduction number. The impact of different parameters of predators is studied. Simulation results show that the performance of our proposed models is effective in combating such worms, in terms of decreasing the the number of hosts infected by the prey and reducing the prey propagation speed.

Predators Combat Good Point Set Scanning-Based Self-Learning Worms

Good point set scanning-based self-learning worms can reach a stupendous propagation speed in virtue of the non-uniform vulnerable-host distribution than that of traditional worms. In order to combat self-learning worms, this paper proposes an interaction model. Using the interaction model, we obtain the basic reproduction number. The impact of different parameters of predators is studied. Simulation results show that the performance of our proposed models is effective in combating such worms, in terms of decreasing the prey infectives and reducing the prey propagation speed.

Worm propagation modeling and analysis on network

In recent years, network worms that had a dramatic increase in the frequency and virulence of such outbreaks have become one of the major threats to the security of the Internet. This paper provides a worm propagation model based on the SEIR deterministic model. The model adopts the birth rate and death rate so that it can provide a more realistic portrait of the worm propagation. In the process of defending worm, dynamic quarantine strategy, dynamic infecting rate and removing rate are adopted. The analysis shows that the worm propagation speed can be efficiently reduced to give people more precious time to defend it. So the negative influence of the worm can be reduced. The simulation results verify the effectiveness of the model.