DDoS attack detection at local area networks using information theoretical metrics

DDoS attacks are one of the major threats to Internet services. Sophisticated hackers are mimicking the features of legitimate network events, such as flash crowds, to fly under the radar. This poses great challenges to detect DDoS attacks. In this paper, we propose an attack feature independent DDoS flooding attack detection method at local area networks. We employ flow entropy on local area network routers to supervise the network traffic and raise potential DDoS flooding attack alarms when the flow entropy drops significantly in a short period of time. Furthermore, information distance is employed to differentiate DDoS attacks from flash crowds. In general, the attack traffic of one DDoS flooding attack session is generated by many bots from one botnet, and all of these bots are executing the same attack program. As a result, the similarity among attack traffic should higher than that among flash crowds, which are generated by many random users. Mathematical models have been established for the proposed detection strategies. Analysis based on the models indicates that the proposed methods can raise the alarm for potential DDoS flooding attacks and can differentiate DDoS flooding attacks from flash crowds with conditions. The extensive experiments and simulations confirmed the effectiveness of our proposed detection strategies.

Stable isotope-based community metrics as a tool to identify patterns in food web structure in east African estuaries

1.Quantitative tools to describe biological communities are important for conservation and ecological management. The analysis of trophic structure can be used to quantitatively describe communities. Stable isotope analysis is useful to describe trophic organization, but statistical models that allow the identification of general patterns and comparisons between systems/sampling periods have only recently been developed. 2.Here, stable isotope-based Bayesian community-wide metrics are used to investigate patterns in trophic structure in five estuaries that differ in size, sediment yield and catchment vegetation cover (C3/C4): the Zambezi in Mozambique, the Tana in Kenya and the Rianila, the Betsiboka and Pangalanes Canal (sampled at Ambila) in Madagascar. 3.Primary producers, invertebrates and fish of different trophic ecologies were sampled at each estuary before and after the 2010–2011 wet season. Trophic length, estimated based on δ15N, varied between 3·6 (Ambila) and 4·7 levels (Zambezi) and did not vary seasonally for any estuary. Trophic structure differed the most at Ambila, where trophic diversity and trophic redundancy were lower than at the other estuaries. Among the four open estuaries, the Betsiboka and Tana (C4-dominated) had lower trophic diversity than the Zambezi and Rianila (C3-dominated), probably due to the high loads of suspended sediment, which limited the availability of aquatic sources. 4.There was seasonality in trophic structure at Ambila and Betsiboka, as trophic diversity increased and trophic redundancy decreased from the prewet to the postwet season. For Ambila, this probably resulted from the higher variability and availability of sources after the wet season, which allowed diets to diversify. For the Betsiboka, where aquatic productivity is low, this was likely due to a greater input of terrestrial material during the wet season. 5.The comparative analysis of community-wide metrics was useful to detect patterns in trophic structure and identify differences/similarities in trophic organization related to environmental conditions. However, more widespread application of these approaches across different faunal communities in contrasting ecosystems is required to allow identification of robust large-scale patterns in trophic structure. The approach used here may also find application in comparing food web organization before and after impacts or monitoring ecological recovery after rehabilitation.

Metrics to assess ecological condition, change, and impacts in sandy beach ecosystems

Complexity is increasingly the hallmark in environmental management practices of sandy shorelines. This arises primarily from meeting growing public demands (e.g., real estate, recreation) whilst reconciling economic demands with expectations of coastal users who have modern conservation ethics. Ideally, shoreline management is underpinned by empirical data, but selecting ecologically-meaningful metrics to accurately measure the condition of systems, and the ecological effects of human activities, is a complex task. Here we construct a framework for metric selection, considering six categories of issues that authorities commonly address: erosion; habitat loss; recreation; fishing; pollution (litter and chemical contaminants); and wildlife conservation. Possible metrics were scored in terms of their ability to reflect environmental change, and against criteria that are widely used for judging the performance of ecological indicators (i.e., sensitivity, practicability, costs, and public appeal). From this analysis, four types of broadly applicable metrics that also performed very well against the indicator criteria emerged: 1.) traits of bird populations and assemblages (e.g., abundance, diversity, distributions, habitat use); 2.) breeding/reproductive performance sensu lato (especially relevant for birds and turtles nesting on beaches and in dunes, but equally applicable to invertebrates and plants); 3.) population parameters and distributions of vertebrates associated primarily with dunes and the supralittoral beach zone (traditionally focused on birds and turtles, but expandable to mammals); 4.) compound measurements of the abundance/cover/biomass of biota (plants, invertebrates, vertebrates) at both the population and assemblage level. Local constraints (i.e., the absence of birds in highly degraded urban settings or lack of dunes on bluff-backed beaches) and particular issues may require alternatives. Metrics - if selected and applied correctly - provide empirical evidence of environmental condition and change, but often do not reflect deeper environmental values per se. Yet, values remain poorly articulated for many beach systems; this calls for a comprehensive identification of environmental values and the development of targeted programs to conserve these values on sandy shorelines globally.

Is there an interaction between socioeconomic status and FRAX 10-year fracture probability determined with and without bone density measures? Data from the Geelong Osteoporosis Study of female cohort.

FRAX(©) evaluates 10-year fracture probabilities and can be calculated with and without bone mineral density (BMD). Low socioeconomic status (SES) may affect BMD, and is associated with increased fracture risk. Clinical risk factors differ by SES; however, it is unknown whether aninteraction exists between SES and FRAX determined with and without the BMD. From the Geelong Osteoporosis Study, we drew 819 females aged ≥50 years. Clinical data were collected during 1993-1997. SES was determined by cross-referencing residential addresses with Australian Bureau of Statistics census data and categorized in quintiles. BMD was measured by dual energy X-ray absorptiometry at the same time as other clinical data were collected. Ten-year fracture probabilities were calculated using FRAX (Australia). Using multivariable regression analyses, we examined whether interactions existed between SES and 10-year probability for hip and any major osteoporotic fracture (MOF) defined by use of FRAX with and without BMD. We observed a trend for a SES * FRAX(no-BMD) interaction term for 10-year hip fracture probability (p = 0.09); however, not for MOF (p = 0.42). In women without prior fracture (n = 518), we observed a significant SES * FRAX(no-BMD) interaction term for hip fracture (p = 0.03) and MOF (p = 0.04). SES does not appear to have an interaction with 10-year fracture probabilities determined by FRAX with and without BMD in women with previous fracture; however, it does appear to exist for those without previous fracture.

Default probability for the Jordanian companies: A test of cash flow theory

Abstract
This paper aims to investigate the effect of cash flow and free cash flow on corporate failure in the emerging market in particular Jordan using two samples; matched sample and a cross sectional time-series (panel data) sample representative of 167 Jordanian companies in 1989-2003. LOGIT models are used to outline the relationship between firms’ financial health and the probability of default. Our results show that there is firm’s free cash flow increases corporate failure. The result also shows that the firm’s cash flow decreases corporate failure. Firms’ capital structures are fund a mental in predicting default. Capital structure is seen as the main factor affecting the probability of default as it affects a firm’s ability to access external sources of funds. Jordanian firms depend on short-term debt for both short and long term financing.

Climatic, vegetation and edaphic influences on the probability of fire across mediterranean woodlands of south-eastern Australia

 Aim: We investigated how the probability of burning is influenced by the time since fire (TSF) and gradients of climate, soil and vegetation in the fire-prone mediterranean-climate mallee woodlands of south-eastern Australia. This provided insight into the processes controlling contemporary fuel dynamics and fire regimes across biogeographical boundaries, and the consequent effects of climate change on potential shifts in boundaries between fuel systems and fire regimes, at a subcontinental scale. Location: South-eastern Australia. Methods: A desktop-based GIS was used to generate random sampling points across the study region to collect data on intersecting fire interval, rainfall, vegetation and soil type. We used a Bayesian framework to examine the effects of combinations of rainfall, vegetation and soil type on the hazard-of-burning and survival parameters of the Weibull distribution. These analyses identify the nature of environmental controls on the length of fire intervals and the age-dependence of the hazard of burning. Results: Higher rainfall was consistently associated with shorter fire intervals. Within a single level of rainfall, however, the interaction between soil and vegetation type influenced the length of fire intervals. Higher-fertility sands were associated with shorter fire intervals in grass-dominated communities, whereas lower-fertility sands were associated with shorter fire intervals in shrub-dominated communities. The hazard of burning remained largely independent of TSF across the region, only markedly increasing with TSF in shrub-dominated communities at high rainfall. Main conclusions: Rainfall had a dominant influence on fire frequency in the mediterranean-climate mallee woodlands of south-eastern Australia. Predicted changes in the spatial distribution and amount of rainfall therefore have the potential to drive changes in fire regimes, although the effects of soil fertility and rainfall on fire regimes do not align on a simple productivity gradient. Reduced soil fertility may favour plant traits that increase the rate of woody litter fuel accumulation and flammability, which may alter the overriding influence of rainfall gradients on fire regimes.

Dimensions and metrics for evaluating recommendation systems

Recommendation systems support users and developers of various computer and software systems to overcome information overload, perform information discovery tasks, and approximate computation, among others. They have recently become popular and have attracted a wide variety of application scenarios ranging from business process modeling to source code manipulation. Due to this wide variety of application domains, different approaches and metrics have been adopted for their evaluation. In this chapter, we review a range of evaluation metrics and measures as well as some approaches used for evaluating recommendation systems. The metrics presented in this chapter are grouped under sixteen different dimensions, e.g., correctness, novelty, coverage. We review these metrics according to the dimensions to which they correspond. A brief overview of approaches to comprehensive evaluation using collections of recommendation system dimensions and associated metrics is presented. We also provide suggestions for key future research and practice directions.

Detecting stepping stones by abnormal causality probability

Locating the real source of the Internet attacks has long been an important but difficult problem to be addressed. In the real world, attackers can easily hide their identities and evade punishment by relaying their attacks through a series of compromised systems or devices called stepping stones. Currently, researchers mainly use similar features from the network traffic, such as packet timestamps and frequencies, to detect stepping stones. However, these features can be easily destroyed by attackers using evasive techniques. In addition, it is also difficult to implement an appropriate threshold of similarity that can help justify the stepping stones. In order to counter these problems, in this paper, we introduce the consistent causality probability to detect the stepping stones. We formulate the ranges of abnormal causality probabilities according to the different network conditions, and on the basis of it, we further implement to self-adaptive methods to capture stepping stones. To evaluate our proposed detection methods, we adopt theoretic analysis and empirical studies, which demonstrate accuracy of the abnormal causality probability. Moreover, we compare our proposed methods with previous works. The result shows that our methods in this paper significantly outperform previous works in the accuracy of detection malicious stepping stones, even when evasive techniques are adopted by attackers.

Marketing Metrics : um estudo exploratório sobre a construção do conhecimento de um novo tema em marketing

Este trabalho constitui-se em um estudo acerca da construção do conhecimento do tema Marketing Metrics dentro da disciplina de marketing, centrando-se na linha de pesquisa de Valor do Cliente, uma das cinco principais que estão sendo trabalhadas sobre o tema. Assim, o autor deste trabalho realizou um estudo exploratório dividido em duas etapas, uma de análise da bibliografia acerca do Marketing Metrics em diversos centros acadêmicos e outra de verificação empresarial para analisar o grau de conhecimento e avaliação da importância do tema na visão empresarial. Ao final, o autor chega a um modelo sobre a construção de conhecimento do tema pesquisado e suposições a serem futuramente testadas, incluindo a influência de fatores como a natureza do negócio em que está inserida, o tamanho da base de clientes, a necessidade de uso do produto ou serviço, as barreiras de saída e o tamanho da empresa no grau de necessidade de relacionamento com os clientes, bem como a influência deste na busca do conhecimento acadêmico.

Bounds for the probability distribution function of the linear ACD process

This paper derives both lower and upper bounds for the probability distribution function of stationary ACD(p, q) processes. For the purpose of illustration, I specialize the results to the main parent distributions in duration analysis. Simulations show that the lower bound is much tighter than the upper bound.

Integral representation with convex capacities that are squeeze of (additive) probability measures

In this paper I will investigate the conditions under which a convex capacity (or a non-additive probability which exhibts uncertainty aversion) can be represented as a squeeze of a(n) (additive) probability measure associate to an uncertainty aversion function. Then I will present two alternatives forrnulations of the Choquet integral (and I will extend these forrnulations to the Choquet expected utility) in a parametric approach that will enable me to do comparative static exercises over the uncertainty aversion function in an easy way.

Risky business: social media metrics and political risk analysis

A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de “big data” de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.

Contribuições aos Processos de Clustering com Base em Métricas não-Euclidianas

In this work we present a new clustering method that groups up points of a data set in classes. The method is based in a algorithm to link auxiliary clusters that are obtained using traditional vector quantization techniques. It is described some approaches during the development of the work that are based in measures of distances or dissimilarities (divergence) between the auxiliary clusters. This new method uses only two a priori information, the number of auxiliary clusters Na and a threshold distance dt that will be used to decide about the linkage or not of the auxiliary clusters. The number os classes could be automatically found by the method, that do it based in the chosen threshold distance dt, or it is given as additional information to help in the choice of the correct threshold. Some analysis are made and the results are compared with traditional clustering methods. In this work different dissimilarities metrics are analyzed and a new one is proposed based on the concept of negentropy. Besides grouping points of a set in classes, it is proposed a method to statistical modeling the classes aiming to obtain a expression to the probability of a point to belong to one of the classes. Experiments with several values of Na e dt are made in tests sets and the results are analyzed aiming to study the robustness of the method and to consider heuristics to the choice of the correct threshold. During this work it is explored the aspects of information theory applied to the calculation of the divergences. It will be explored specifically the different measures of information and divergence using the Rényi entropy. The results using the different metrics are compared and commented. The work also has appendix where are exposed real applications using the proposed method