Data Reduction in Intrusion Alert Correlation

Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.

Credible Commitments and Post-Conflict Refugee Return: A Statistical and Network Analysis

I examine determinants of refugee return after conflicts. I argue that institutional constraints placed on the executive provide a credible commitment that signals to refugees that the conditions required for durable return will be created. This results in increased return flows for refugees. Further, when credible commitments are stronger in the country of origin than in the country of asylum, the level of return increases. Finally, I find that specific commitments made to refugees in the peace agreement do not lead to increased return because they are not credible without institutional constraints. Using data on returnees that has only recently been made available, along with network analysis and an original coding of the provisions in refugee agreements, statistical results are found to support this theory. An examination of cases in Djibouti, Sierra Leone, and Liberia provides additional support for this argument.

D3M: multicast listener mobility support mechanisms over distributed mobility anchoring architectures

The explosion in mobile data traffic is a driver for future network operator technologies, given its large potential to affect both network performance and generated revenue. The concept of distributed mobility management (DMM) has emerged in order to overcome efficiency-wise limitations in centralized mobility approaches, proposing not only the distribution of anchoring functions but also dynamic mobility activation sensitive to the applications needs. Nevertheless, there is not an acceptable solution for IP multicast in DMM environments, as the first proposals based on MLD Proxy are prone to tunnel replication problem or service disruption. We propose the application of PIM-SM in mobility entities as an alternative solution for multicast support in DMM, and introduce an architecture enabling mobile multicast listeners support over distributed anchoring frameworks in a network-efficient way. The architecture aims at providing operators with flexible options to provide multicast mobility, supporting three modes: the first one introduces basic IP multicast support in DMM; the second improves subscription time through extensions to the mobility protocol, obliterating the dependence on MLD protocol; and the third enables fast listener mobility by avoiding potentially slow multicast tree convergence latency in larger infrastructures, by benefiting from mobility tunnels. The different modes were evaluated by mathematical analysis regarding disruption time and packet loss during handoff against several parameters, total and tunneling packet delivery cost, and regarding packet and signaling overhead.

Network analysis approach to find new candidate genes and pathways involved in the pathophysiology of familial hypercholesterolemia

Still a big gap exists between clinical and genetic diagnosis of dyslipidemic disorders. Almost the 60% of the patients with a clinical diagnosis of Familial hypercholesterolemia (FH) still lack of a genetic diagnosis. Here we present the preliminary results of an integrative approach intended to identify new candidate genes and to dissect pathways that can be dysregulated in the disease. Interesting hits will be subsequently knocked down in vitro in order to evaluate their functional role in the uptake of fluorescently-labeled LDL and free cell cholesterol using automated microscopy.

High fat-fed diabetic mice present with profound alterations of the osteocyte network

International audience

Equilibrium Assignments in Competitive and Cooperative Traffic Flow Routing

Part 18: Optimization in Collaborative Networks

Analysis of a stochastic SIR epidemic on a random network incorporating household structure

This paper is concerned with a stochastic SIR (susceptible-infective-removed) model for the spread of an epidemic amongst a population of individuals, with a random network of social contacts, that is also partitioned into households. The behaviour of the model as the population size tends to infinity in an appropriate fashion is investigated. A threshold parameter which determines whether or not an epidemic with few initial infectives can become established and lead to a major outbreak is obtained, as are the probability that a major outbreak occurs and the expected proportion of the population that are ultimately infected by such an outbreak, together with methods for calculating these quantities. Monte Carlo simulations demonstrate that these asymptotic quantities accurately reflect the behaviour of finite populations, even for only moderately sized finite populations. The model is compared and contrasted with related models previously studied in the literature. The effects of the amount of clustering present in the overall population structure and the infectious period distribution on the outcomes of the model are also explored.

TRAFFIC IMPACT ANALYSIS OF SEVERAL DYNAMIC LANE MANAGEMENT STRATEGIES FOR CONGESTION MITIGATION BASED ON DTA MODEL

Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.

Quantifying the Resilience of an Urban Traffic-Electric Power Coupled System

Transportation system resilience has been the subject of several recent studies. To assess the resilience of a transportation network, however, it is essential to model its interactions with and reliance on other lifelines. In this work, a bi-level, mixed-integer, stochastic program is presented for quantifying the resilience of a coupled traffic-power network under a host of potential natural or anthropogenic hazard-impact scenarios. A two-layer network representation is employed that includes details of both systems. Interdependencies between the urban traffic and electric power distribution systems are captured through linking variables and logical constraints. The modeling approach was applied on a case study developed on a portion of the signalized traffic-power distribution system in southern Minneapolis. The results of the case study show the importance of explicitly considering interdependencies between critical infrastructures in transportation resilience estimation. The results also provide insights on lifeline performance from an alternative power perspective.

Analysis of english teachers' perceptions related to strategies studied in a in-service course in Cuenca

El presente estudio describe las percepciones de los profesores fiscales de inglés en relación a las estrategias aprendidas durante una capacitación realizada en el año 2012 por un grupo de investigadores de la Facultad de Filosofía de la Universidad de Cuenca. En el año 2014, este grupo de investigadores inició un proyecto para analizar el impacto de dicha capacitación. Este es el marco contextual en el cual se desarrolla el análisis de la percepción docente. La propuesta está basada en el método exploratorio. El instrumento de investigación fue la entrevista personal a diez profesores que participaron de la capacitación en el año 2012. Los resultados fueron analizados con la ayuda del Software Atlas ti. Se identificaron catorce códigos diferentes que fueron agrupados en cuatro grupos de familias: estrategias comunicativas, aprendizaje significativo, percepciones de las necesidades e inconsistencias. Todas estas familias de códigos convergieron alrededor del Aprendizaje Basado en Tareas (ABT), el cual permitía generar un outcome, cuyo significado específico es la generación de un producto a partir del uso del idioma inglés por parte de los estudiantes. Un hallazgo importante fue que casi todos los profesores recordaron varias estrategias aprendidas en la capacitación, mismas que sumaron un total de nueve, además la mitad de docentes estaba usando el outcome en sus clases, ello da cuenta de la percepción positiva que tienen los docentes sobre el curso, a pesar de haber transcurrido dos años de su clausura.

A regulação diante da evolução da essencialidade do serviço público : a reclassificação da banda larga como serviço de telecomunicações nos Estados Unidos

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Direito, Programa de Pós-Graduação em Direito, 2016.