1,720,975 research outputs found
ThePhish: an Automated Open-Source Phishing Email Analysis Platform
No full textPhishing, and specifically phishing emails, are becoming the most pervasive cyberattack and the most widely used infection vector. As a consequence, SOCs, CERTs, and CSIRTs are overwhelmed by the number of emails that they need to analyze every day, with the majority of them being false positives. The manual email analysis is a huge waste of effort. Thus, finding approaches to the full or at least partially automated analysis is crucial. This work aims to present ThePhish, an open-source phishing email analysis platform capable of automating the entire email analysis process, starting from the extraction of the observables from the header and the body of the email to the elaboration of a verdict, which is final in most cases. The framework leverages the effectiveness of important open-source projects, namely, MISP, TheHive and Cortex, to filter out a significant number of false positives. If ThePhish is sure about the maliciousness of the email, it scores it as “malicious”. However, an email sometimes can only be considered suspicious and need further analysis. In these cases, ThePhish offers several features that allow analysts to speed up the analysis process and obtain further details on the suspicious emails
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Machine learning for recognition of individuals from motion capture time series: performance and explainability
No full textIn this paper we describe an ongoing research project in which we investigate the capability of AI-systems to recognize individuals from motion capture data, e.g. using a neural network. In our previous work [1] we also showed which motion features more strongly characterize each individual. In addition, we report on the application of some techniques suggested by Explainable AI's literature. In particular we have analyzed the parsimonious linear fingerprinting (PLiF) [2] and a specific learning shapelets method suggested by Tavenard [3]
Why Can Neural Networks Recognize Us by Our Finger Movements?
No full textNeurobehavioral evidence suggests that human movement may be characterized by relatively stable individual differences (i.e. individual motor signatures or IMS). While most research has focused on the macroscopic level, all attempts to extract IMS have overlooked the fact that functionally relevant discontinuities are clearly visible when zooming into the microstructure of movements. These recurrent (2–3 Hz) speed breaks (sub-movements) reflect an intermittent motor control policy that might provide a far more robust way to identify IMSs. In this study, we show that individuals can be recognized from motion capture data using a neural network. In particular, we trained a classifier (a convolutional neural network) on a data set composed of time series recording the positions of index finger movements of 60 individuals; in tests, the neural network achieves an accuracy of 80%. We also investigated how different pre-processing techniques affect the accuracy in order to assess which motion features more strongly characterize each individual and, in particular, whether the presence of submovements in the data can improve the classifier’s performance
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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