485 research outputs found
WiFi Epidemiology: Can Your Neighbors' Router Make Yours Sick?
In densely populated urban areas WiFi routers form a tightly interconnected
proximity network that can be exploited as a substrate for the spreading of
malware able to launch massive fraudulent attack and affect entire urban areas
WiFi networks. In this paper we consider several scenarios for the deployment
of malware that spreads solely over the wireless channel of major urban areas
in the US. We develop an epidemiological model that takes into consideration
prevalent security flaws on these routers. The spread of such a contagion is
simulated on real-world data for geo-referenced wireless routers. We uncover a
major weakness of WiFi networks in that most of the simulated scenarios show
tens of thousands of routers infected in as little time as two weeks, with the
majority of the infections occurring in the first 24 to 48 hours. We indicate
possible containment and prevention measure to limit the eventual harm of such
an attack.Comment: 22 pages, 1 table, 4 figure
Internet data packet transport: from global topology to local queueing dynamics
We study structural feature and evolution of the Internet at the autonomous
systems level. Extracting relevant parameters for the growth dynamics of the
Internet topology, we construct a toy model for the Internet evolution, which
includes the ingredients of multiplicative stochastic evolution of nodes and
edges and adaptive rewiring of edges. The model reproduces successfully
structural features of the Internet at a fundamental level. We also introduce a
quantity called the load as the capacity of node needed for handling the
communication traffic and study its time-dependent behavior at the hubs across
years. The load at hub increases with network size as .
Finally, we study data packet traffic in the microscopic scale. The average
delay time of data packets in a queueing system is calculated, in particular,
when the number of arrival channels is scale-free. We show that when the number
of arriving data packets follows a power law distribution, ,
the queue length distribution decays as and the average delay
time at the hub diverges as in the limit when , being the network degree
exponent.Comment: 5 pages, 4 figures, submitted to International Journal of Bifurcation
and Chao
Traffic-driven Epidemic Spreading in Finite-size Scale-Free Networks
The study of complex networks sheds light on the relation between the
structure and function of complex systems. One remarkable result is the absence
of an epidemic threshold in infinite-size scale-free networks, which implies
that any infection will perpetually propagate regardless of the spreading rate.
The vast majority of current theoretical approaches assumes that infections are
transmitted as a reaction process from nodes to all neighbors. Here we adopt a
different perspective and show that the epidemic incidence is shaped by traffic
flow conditions. Specifically, we consider the scenario in which epidemic
pathways are defined and driven by flows. Through extensive numerical
simulations and theoretical predictions, it is shown that the value of the
epidemic threshold in scale-free networks depends directly on flow conditions,
in particular on the first and second moments of the betweenness distribution
given a routing protocol. We consider the scenarios in which the delivery
capability of the nodes is bounded or unbounded. In both cases, the threshold
values depend on the traffic and decrease as flow increases. Bounded delivery
provokes the emergence of congestion, slowing down the spreading of the disease
and setting a limit for the epidemic incidence. Our results provide a general
conceptual framework to understand spreading processes on complex networks.Comment: Final version to be published in Proceedings of the National Academy
of Sciences US
Phase transitions in contagion processes mediated by recurrent mobility patterns
Human mobility and activity patterns mediate contagion on many levels,
including the spatial spread of infectious diseases, diffusion of rumors, and
emergence of consensus. These patterns however are often dominated by specific
locations and recurrent flows and poorly modeled by the random diffusive
dynamics generally used to study them. Here we develop a theoretical framework
to analyze contagion within a network of locations where individuals recall
their geographic origins. We find a phase transition between a regime in which
the contagion affects a large fraction of the system and one in which only a
small fraction is affected. This transition cannot be uncovered by continuous
deterministic models due to the stochastic features of the contagion process
and defines an invasion threshold that depends on mobility parameters,
providing guidance for controlling contagion spread by constraining mobility
processes. We recover the threshold behavior by analyzing diffusion processes
mediated by real human commuting data.Comment: 20 pages of Main Text including 4 figures, 7 pages of Supplementary
Information; Nature Physics (2011
Epidemics in partially overlapped multiplex networks
Many real networks exhibit a layered structure in which links in each layer
reflect the function of nodes on different environments. These multiple types
of links are usually represented by a multiplex network in which each layer has
a different topology. In real-world networks, however, not all nodes are
present on every layer. To generate a more realistic scenario, we use a
generalized multiplex network and assume that only a fraction of the nodes
are shared by the layers. We develop a theoretical framework for a branching
process to describe the spread of an epidemic on these partially overlapped
multiplex networks. This allows us to obtain the fraction of infected
individuals as a function of the effective probability that the disease will be
transmitted . We also theoretically determine the dependence of the epidemic
threshold on the fraction of shared nodes in a system composed of two
layers. We find that in the limit of the threshold is dominated by
the layer with the smaller isolated threshold. Although a system of two
completely isolated networks is nearly indistinguishable from a system of two
networks that share just a few nodes, we find that the presence of these few
shared nodes causes the epidemic threshold of the isolated network with the
lower propagating capacity to change discontinuously and to acquire the
threshold of the other network.Comment: 13 pages, 4 figure
Detecting rich-club ordering in complex networks
Uncovering the hidden regularities and organizational principles of networks
arising in physical systems ranging from the molecular level to the scale of
large communication infrastructures is the key issue for the understanding of
their fabric and dynamical properties [1-5]. The ``rich-club'' phenomenon
refers to the tendency of nodes with high centrality, the dominant elements of
the system, to form tightly interconnected communities and it is one of the
crucial properties accounting for the formation of dominant communities in both
computer and social sciences [4-8]. Here we provide the analytical expression
and the correct null models which allow for a quantitative discussion of the
rich-club phenomenon. The presented analysis enables the measurement of the
rich-club ordering and its relation with the function and dynamics of networks
in examples drawn from the biological, social and technological domains.Comment: 1 table, 3 figure
Risk factors for obstructive sleep apnea syndrome in children: state of the art
The obstructive sleep apnea syndrome (OSAS) represents only part of a large group of pathologies of variable entity called respiratory sleep disorders (RSD) which include simple snoring and increased upper airway resistance syndrome (UARS). Although the etiopathogenesis of adult OSAS is well known, many aspects of this syndrome in children are still debated. Its prevalence is about 2% in children from 2 to 8 years of age, mostly related to the size of the upper airways adenoid tissue. Several risk factors linked to the development of OSAS are typical of the pediatric age. The object of this paper is to analyze the state of the art on this specific topic, discussing its implications in terms of diagnosis and management
Multiscale mobility networks and the large scale spreading of infectious diseases
Among the realistic ingredients to be considered in the computational
modeling of infectious diseases, human mobility represents a crucial challenge
both on the theoretical side and in view of the limited availability of
empirical data. In order to study the interplay between small-scale commuting
flows and long-range airline traffic in shaping the spatio-temporal pattern of
a global epidemic we i) analyze mobility data from 29 countries around the
world and find a gravity model able to provide a global description of
commuting patterns up to 300 kms; ii) integrate in a worldwide structured
metapopulation epidemic model a time-scale separation technique for evaluating
the force of infection due to multiscale mobility processes in the disease
dynamics. Commuting flows are found, on average, to be one order of magnitude
larger than airline flows. However, their introduction into the worldwide model
shows that the large scale pattern of the simulated epidemic exhibits only
small variations with respect to the baseline case where only airline traffic
is considered. The presence of short range mobility increases however the
synchronization of subpopulations in close proximity and affects the epidemic
behavior at the periphery of the airline transportation infrastructure. The
present approach outlines the possibility for the definition of layered
computational approaches where different modeling assumptions and granularities
can be used consistently in a unifying multi-scale framework.Comment: 10 pages, 4 figures, 1 tabl
Tympanic cholesterol granuloma and exclusive endoscopic approach
Objective: Background: Case Report: Conclusions: Unusual or unexpected effect of treatment Cholesterol granuloma is a histological entity containing cholesterol crystals surrounded by foreign-body giant cells and chronic inflammation. Tympanic cholesterol granuloma is a rare disease, while petrous bone cholesterol granuloma is more common. Surgery consists of elective management in most cases of CGs. There are several types of surgery described to treat cholesterol granuloma; however, a case treated by primary endoscopic ear surgery has not yet been described. The aim of this case report is to present the endoscopic characteristics of cholesterol granulomas and show how endoscopic ear surgery is possible in isolated and selected cases with this pathology. We report the case of a 65-year-old patient affected by a cholesterol granuloma of the middle ear, with progressive hearing impairment and fullness of the left ear. The granuloma was diagnosed via medical imaging using magnetic resonance imaging, which identified the typical high signal intensity in T1-and T2-weighted images. In this case, cholesterol granuloma was limited to the epitympanic and mesotympanic regions. For small cholesterol granulomas confined to the middle ear, a canal wall-up or wall-down tympanoplasty plus ventilation tube insertion are usually performed. In this case, primary endoscopic surgery was performed under general anaesthesia to remove the presumed cholesterol granuloma. It was completely removed by this approach, without facial nerve injuries or postoperative complications. The patient had no disease recurrence at clinical and radiological investigation at 1-year follow-up. An exclusive endoscopic approach to remove cholesterol granuloma is feasible. However, it should only be performed in selected cases
Network Structures from Selection Principles
We present an analysis of the topologies of a class of networks which are
optimal in terms of the requirements of having as short a route as possible
between any two nodes while yet keeping the congestion in the network as low as
possible. Strikingly, we find a variety of distinct topologies and novel phase
transitions between them on varying the number of links per node. Our results
suggest that the emergence of the topologies observed in nature may arise both
from growth mechanisms and the interplay of dynamical mechanisms with a
selection process.Comment: 4 pages, 5 figure
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