Error and attack tolerance of evolving networks with local preferential attachment

Sun, Shiwen; Liu, Zhongxin; Chen, Zengqiang; Yuan, Zhen

doi:10.1016/j.physa.2006.05.049

Cited by 56 publications

(40 citation statements)

References 20 publications

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“…2 that the degree of network heterogeneity grows with M and this result is also consistent with the very recent work of Sun et al [19]. All these results are averaged over 100 network implementations in Figs.…”

Section: Introductionsupporting

confidence: 90%

“…The localworld model displays a transition from the exponential distribution to the power-law distribution and captures an important feature in the real-world network: preferential attachment mechanism that works only within a localworld instead of the whole network, such as communication networks, world trade web and biological networks [18]. A recent work [19] also indicates that numerous statistical characteristics of this model, such as clustering coefficient, diameter, efficiency, error and attack tolerance, are all closely correlated with local-world size (M). Is the epidemic spreading with time delay also related with this parameter?…”

Section: Introductionmentioning

confidence: 99%

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Epidemic spreading behavior with time delay on local-world evolving networks

Xia

Liu

Chen

et al. 2008

Front. Electr. Electron. Eng. Ch

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An improved susceptible-infected-susceptible (SIS) model in the local-world evolving network model is presented to study the epidemic spreading behavior with time delay, which is added into the infected phase. The local-world evolving model displays a transition from the exponential network to the scale-free network with respect to the degree distribution. Two typical delay regimes, i.e., uniform and degree-dependent delays are incorporated into the SIS epidemic model to investigate the epidemic infection processes in the local-world network model. The results indicate that the infection delay will promote the epidemic outbreaks, increase the prevalence and reduce the critical threshold of epidemic spreading. It is also found that local-world size M will considerably influence the epidemic spreading behavior with time delay in the local-world network through large-scale numerical simulations. Simulation results are also of relevance to fight epidemic outbreaks.

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Section: Introductionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Epidemic spreading behavior with time delay on local-world evolving networks

Xia

Liu

Chen

et al. 2008

Front. Electr. Electron. Eng. Ch

Self Cite

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“…Since the degree distributions in the carding social networks are lognormal, this means that there are less highly connected nodes and more moderately connected nodes [2]. This implies that the networks are more robust against targeted attacks than scale-free networks as well as more resilient against random node removals than random networks [26]. However, targeted attacks remain particularly suitable against carding social networks because they are disassortatively mixed, which means that high-and mediumdegree nodes (e.g.…”

Section: Implications and Discussionmentioning

confidence: 99%

Structural analysis of online criminal social networks

Yip

Shadbolt

Webber

2012

2012 IEEE International Conference on Intelligence and Security Informatics

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Abstract-Over the last decade, a sophisticated underground economy has emerged over the Internet in which cybercriminals collaborate and trade different goods and services. This study takes a unique approach towards understanding the functioning of the underground economy by focusing on the social dynamics between the cybercriminals. Using anonymized private messaging records from four underground forums formerly operating as online black markets, this study aims to examine the structural properties of the networks of personal interactions between the cybercriminals and to turn the findings into actionable intelligence for tackling the problem of profit-driven cybercrime.

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“…In the first part, we evaluate the global network connectivity by measuring how many nodes can be disconnected from a network without disrupting the network. In the second part, we evaluate the local network connectivity and communication efficiency when a certain number of nodes leaving from the original global network [19].…”

Section: B a Methods To Construct A Bimodal Networkmentioning

confidence: 99%

Designing P2P Networks Tolerant to Attacks and Faults Based on Bimodal Degree Distribution

Suto¹,

Nishiyama²,

Shen³

et al. 2012

JCM

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Abstract-Recently, in contrast with the centralized networks (e.g., traditional client/server systems), the distributed networks such as Peer-to-Peer (P2P) networks and grid networks have attracted much attention due to their scalability. While the distributed networks have the advantage of allowing the node(s) to join or leave the network easily, the issue of lack of resiliency to both attacks and faults still remains. In this paper, we classify the existing distributed networks based on their degree distributions. Then, we demonstrate that they are not resilient to attacks and/or faults. For example, unstructured P2P networks, which have a power-law degree distribution, are vulnerable to attacks such as DOS. To address and resolve this issue, we propose a method to construct a network following bimodal degree distribution, which is robust to deal with both attacks and faults. Performance evaluation is conducted through computer simulations, which show that the proposed method can achieve higher resilience compared with other existing networking approaches.Index Terms-P2P networks, overlay networks, attack and fault tolerance, degree distribution.

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Error and attack tolerance of evolving networks with local preferential attachment

Cited by 56 publications

References 20 publications

Epidemic spreading behavior with time delay on local-world evolving networks

Epidemic spreading behavior with time delay on local-world evolving networks

Structural analysis of online criminal social networks

Designing P2P Networks Tolerant to Attacks and Faults Based on Bimodal Degree Distribution

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