Locating defense positions for thwarting the propagation of topological worms

A common view for the preferable positions of thwarting worm propagation is at the highly connected nodes. However, in certain conditions, such as when some popular users (highly connected nodes in the network) have more vigilance on the malicious codes, this may not always be the truth. In this letter, we propose a measure of betweenness and closeness to locate the most suitable positions for slowing down the worm propagation. This work provides practical values to the defense of topological worms.

Graphene oxide nanoparticles as a nonbleaching optical probe for two-photon luminescence imaging and cell therapy

Lasting glow: Under femtosecond laser irradiation, graphene oxide nanoparticles (GONs) give strong two-photon luminescence (TPL; see picture). The presence of GONs also induces microbubbling, which causes cell death at an order of magnitude lower laser power than when cells are not labeled. The results show that GONs can be used for TPL-based imaging and photothermal cancer therapy.

Modeling and defense against propagation of worms in networks

Worms are widely believed to be one of the most serious challenges in network security research. In order to prevent worms from propagating, we present a microcosmic model, which can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

Effects of social characters in viral propagation seeding strategies in online social networks

Online social networks have not only become a point of aggregation and exchange of information, they have so radically rooted into our everyday behaviors that they have become the target of important network attacks. We have seen an increasing trend in Sybil based activity, such as in personification, fake profiling and attempts to maliciously subvert the community stability in order to illegally create benefits for some individuals, such as online voting, and also from more classic informatics assaults using specifically mutated worms. Not only these attacks, in the latest months, we have seen an increase in spam activities on social networks such as Facebook and RenRen, and most importantly, the first attempts at propagating worms within these communities. What differentiates these attacks from normal network attacks, is that compared to anonymous and stealthy activities, or by commonly untrusted emails, social networks regain the ability to propagate within consentient users, who willingly accept to partake. In this paper, we will demonstrate the effects of influential nodes against non-influential nodes through in simulated scenarios and provide an overview and analysis of the outcomes.

Generalized coupled photon transport equations for handling correlated photon streams with distinct frequencies

A generalized form of coupled photon transport equations that can handle correlated light beams with distinct frequencies is introduced. The derivation is based on the principle of energy conservation. For a single frequency, the current formulation reduces to a standard photon transport equation, and for fluorescence and phosphorescence, the diffusion models derived from the proposed photon transport model match for homogenous media. The generalized photon transport model is extended to handle wideband inputs in the frequency domain. © 2012 Optical Society of America.

An analytical model on the propagation of modern email worms

Email worms propagate across networks by taking advantage of email relationships. Modeling the propagation of email worms can help predict their potential damages and develop countermeasures. We propose a novel analytical model on the propagation process of modern reinfection email worms. It relies on probabilistic analysis, and thus can provide a steady and reliable assessment on the propagation dynamics. Additionally, by introducing virtual users to represent the repetitious spreading process, the proposed model overcomes the computational challenge caused by reinfection processes. To demonstrate the benefits of our model, we conduct a series of experimental evaluation. The results show that our novel approach achieves a greater accuracy and is more suitable for modeling modern email worms than previous models.

Modeling propagation dynamics of social network worms

Social network worms, such as email worms and facebook worms, pose a critical security threat to the Internet. Modeling their propagation dynamics is essential to predict their potential damages and develop countermeasures. Although several analytical models have been proposed for modeling propagation dynamics of social network worms, there are two critical problems unsolved: temporal dynamics and spatial dependence. First, previous models have not taken into account the different time periods of Internet users checking emails or social messages, namely, temporal dynamics. Second, the problem of spatial dependence results from the improper assumption that the states of neighboring nodes are independent. These two problems seriously affect the accuracy of the previous analytical models. To address these two problems, we propose a novel analytical model. This model implements a spatial-temporal synchronization process, which is able to capture the temporal dynamics. Additionally, we find the essence of spatial dependence is the spreading cycles. By eliminating the effect of these cycles, our model overcomes the computational challenge of spatial dependence and provides a stronger approximation to the propagation dynamics. To evaluate our susceptible-infectious-immunized (SII) model, we conduct both theoretical analysis and extensive simulations. Compared with previous epidemic models and the spatial-temporal model, the experimental results show our SII model achieves a greater accuracy. We also compare our model with the susceptible-infectious-susceptible and susceptible-infectious- recovered models. The results show that our model is more suitable for modeling the propagation of social network worms.

Modeling malware propagation in smartphone social networks

Smartphones have become an integral part of our everyday lives, such as online information accessing, SMS/MMS, social networking, online banking, and other applications. The pervasive usage of smartphones also results them in enticing targets of hackers and malware writers. This is a desperate threat to legitimate users and poses considerable challenges to network security community. In this paper, we model smartphone malware propagation through combining mathematical epidemics and social relationship graph of smartphones. Moreover, we design a strategy to simulate the dynamic of SMS/MMS-based worm propagation process from one node to an entire network. The strategy integrates infection factor that evaluates the propagation degree of infected nodes, and resistance factor that offers resistance evaluation towards susceptible nodes. Extensive simulations have demonstrated that the proposed malware propagation model is effective and efficient.

Modeling the propagation and defense study of internet malicious information

 Dr. Wen's research includes modelling the propagation dynamics of malicious information, exposing the most influential people and source identification of epidemics in social networks. His research is beneficial to both academia and industry in the field of Internet social networks.