Toward a phishing attack ontology

Phishing attacks are the most common form of social engineering where attackers intend to deceive targeted people into revealing sensitive information or installing malware. To understand the dynamics of phishing attacks and design suitable countermeasures, particularly the promotion of phishing awareness, cybersecurity researchers have proposed several domain conceptual models and lightweight ontologies. Despite the growing literature in ontology engineering highlighting the advantages of employing upper and reference ontologies for domain modeling, current phishing attack models lack ontological foundations. As a result, they suffer from a number of shortcomings, such as false agreements, informality, and limited interoperability. To address this gap, we propose a Phishing Attack Ontology (PHATO) grounded in the Reference Ontology for Security Engineering (ROSE) and the Common Ontology of Value and Risk (COVER), which are both founded in the Unified Foundational Ontology (UFO). Our proposal is represented through the OntoUML ontology-driven conceptual modeling language, benefiting from its ecosystem of tools and domain ontologies. We also discuss some implications of PHATO for the design of anti-phishing countermeasures.</p

Social Eavesdropping in Zebrafish: Tuning of Attention to Social Interactions

Group living animals may eavesdrop on signalling interactions between conspecifics in order to collect adaptively relevant information obtained from others, without incurring in the costs of first-hand information acquisition. This ability (aka social eavesdropping) is expected to impact Darwinian fitness, and hence predicts the evolution of cognitive processes that enable social animals to use public information available in the environment. These adaptive specializations in cognition may have evolved both at the level of learning and memory mechanisms, and at the level of input mechanisms, such as attention, which select the information that is available for learning. Here we used zebrafish to test if attention in a social species is tuned to the exchange of information between conspecifics. Our results show that zebrafish are more attentive towards interacting (i.e. fighting) than towards non-interacting pairs of conspecifics, with the exposure to fighting not increasing activity or stress levels. Moreover, using video playbacks to manipulate form features of the fighting fish, we show that during the assessment phase of the fight, bystanders' attention is more driven by form features of the interacting opponents; whereas during the post-resolution phase, it is driven by biological movement features of the dominant fish chasing the subordinate fish.FCT fellowship: (SFRH/BD/33280/2007), Champalimaud Neuroscience Programme

Social dominance modulates eavesdropping in zebrafish

Group living animals may eavesdrop on signalling interactions between conspecifics and integrate it with their own past social experience in order to optimize the use of relevant information from others. However, little is known about this interplay between public (eavesdropped) and private social information. To investigate it, we first manipulated the dominance status of bystander zebrafish. Next, we either allowed or prevented bystanders from observing a fight. Finally, we assessed their behaviour towards the winners and losers of the interaction, using a custom-made video-tracking system and directional analysis. We found that only dominant bystanders who had seen the fight revealed a significant increase in directional focus (a measure of attention) towards the losers of the fights. Furthermore, our results indicate that information about the fighters' acquired status was collected from the signalling interaction itself and not from post-interaction status cues, which implies the existence of individual recognition in zebrafish. Thus, we show for the first time that zebrafish, a highly social model organism, eavesdrop on conspecific agonistic interactions and that this process is modulated by the eavesdroppers' dominance status. We suggest that this type of integration of public and private information may be ubiquitous in social learning processes.FCT PhD fellowship: (SFRH/BD/33280/2007), Champalimaud Neuroscience Programme

Physics of Psychophysics: Stevens and Weber-Fechner laws are transfer functions of excitable media

Sensory arrays made of coupled excitable elements can improve both their input sensitivity and dynamic range due to collective non-linear wave properties. This mechanism is studied in a neural network of electrically coupled (e.g. via gap junctions) elements subject to a Poisson signal process. The network response interpolates between a Weber-Fechner logarithmic law and a Stevens power law depending on the relative refractory period of the cell. Therefore, these non-linear transformations of the input level could be performed in the sensory periphery simply due to a basic property: the transfer function of excitable media.Comment: 4 pages, 5 figure

Methodology evaluation of pin microrelief meter

The effects of natural weathering and different managements performed in agriculture may best be understood by studying the soil roughness. The aim of this study was to evaluate the optimization of the use of pin microrelief meter, an instrument used to determine the soil surface roughness, as the number of readings collected over traditional methodology proposed in the bibliography. The study was conducted in Rio Paranaiba (MG), in a Haplustox soil. The experimental design was completely randomized in a 2×3 factorial design with four replications. There were combined two types of primary tillage: conventional tillage with disc plow (PCAD) and harrow (PCGA), and three amounts of readings (100, 200, and 300 reading points) sampled in each experimental unit. Independently of the soil tillage, disc plow and harrow, the collection of 100 readings using a pin microrelief meter of a square meter, was sufficient to determine the surface roughness before and after soil preparation, without accuracy loss compared with the traditional method

Copycat CNN: Stealing Knowledge by Persuading Confession with Random Non-Labeled Data

In the past few years, Convolutional Neural Networks (CNNs) have been achieving state-of-the-art performance on a variety of problems. Many companies employ resources and money to generate these models and provide them as an API, therefore it is in their best interest to protect them, i.e., to avoid that someone else copies them. Recent studies revealed that state-of-the-art CNNs are vulnerable to adversarial examples attacks, and this weakness indicates that CNNs do not need to operate in the problem domain (PD). Therefore, we hypothesize that they also do not need to be trained with examples of the PD in order to operate in it. Given these facts, in this paper, we investigate if a target black-box CNN can be copied by persuading it to confess its knowledge through random non-labeled data. The copy is two-fold: i) the target network is queried with random data and its predictions are used to create a fake dataset with the knowledge of the network; and ii) a copycat network is trained with the fake dataset and should be able to achieve similar performance as the target network. This hypothesis was evaluated locally in three problems (facial expression, object, and crosswalk classification) and against a cloud-based API. In the copy attacks, images from both non-problem domain and PD were used. All copycat networks achieved at least 93.7% of the performance of the original models with non-problem domain data, and at least 98.6% using additional data from the PD. Additionally, the copycat CNN successfully copied at least 97.3% of the performance of the Microsoft Azure Emotion API. Our results show that it is possible to create a copycat CNN by simply querying a target network as black-box with random non-labeled data.Comment: 8 pages, 3 figures, accepted by IJCNN 201

Prevalência de depressão em idosos que freqüentam centros de convivência

O objetivo do estudo foi determinar a prevalência de depressão em idosos que freqüentam centros de convivência. Foi realizado estudo descritivo transversal, de fevereiro a julho de 2001, com idosos de idade igual ou acima de 60 anos, provenientes de centros de convivência de Taguatinga, Brasília, DF. A amostra foi composta de 118 idosos, que foram distribuídos em faixas etárias com intervalos de cinco anos e responderam à Escala de Depressão Geriátrica de Yesavage, versão simplificada com 15 perguntas. Foram realizadas análises de variância entre as faixas etárias, teste de Tukey, com intervalo de confiança de 95%. Houve predominância do sexo feminino (90%) e a maioria tinha entre 60 e 64 anos (31%). A depressão foi identificada em 36 idosos (31%), 4% apresentaram depressão grave, e desses, todos na faixa entre 60 e 64 anos (14% do grupo). Recomenda-se a criação de programas nacionais com o objetivo de diminuir sintomas depressivos entre os idosos em centros de convivência.The objective of the study was to establish the prevalence rate of depression among the elderly population (those 60 and older) who frequent community centers. From February to July of 2001, a cross-sectional survey was conducted with elderly people from community centers in Taguatinga, Brasilia, FD (Federal District). The sample included 118 elderly people, distributed in five-year age brackets, who responded to a simplified version of the Yesavage Geriatric Depression Scale with 15 questions. Anova and the Tukey test were performed to analyze differences between the age groups with 95% confidence intervals. The sample was predominantly female (90%) with the majority reporting being in the age bracket of 60 to 64 years old (31%). Depression was reported by 36 respondents (31%) and severe depression was reported by 4% of those interviewed, all of whom were in the age bracket of 60 to 64 (representing 14% of this group). National programs should be developed in community centers focused on decreasing depression among the elderly population