1,720,958 research outputs found

    GDPR: When the Right to Access Personal Data Becomes a Threat

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    One year following the entry into force of the GDPR, all websites and data controllers have updated their procedures to store users' data. The GDPR does not only cover how and what data should be saved by the service providers, but it also guarantees an easy way to know what data are collected and the freedom to export them. In this paper, we carry out a comprehensive study on the right to access data provided by Article 15 of the GDPR. We examined more than 300 data controllers, requesting access to personal data to each of them. We found that almost each data controller has a slightly different procedure to fulfill the request and several ways to provide data back to the user, from a structured file like CSV to a screenshot of the monitor. We measure the time needed to complete the access data request and the completeness of the information provided. After this phase of data gathering, we analyze the authentication process followed by the data controllers to establish the identity of the requester. We find that 50.4% of the data controllers that handled the request have flaws in their procedures of identifying users or in their phase of sending the data, exposing users to new threats, even if these data controllers store data in compliance with the GDPR. Our surprising and undesired results show that, in its present deployment, the GDRP has actually decreased the privacy of users of web services

    Cross-domain authorship attribution combining instance-based and profile-based features notebook for PAN at CLEF 2019

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    Being able to identify the author of an unknown text is crucial. Although it is a well-studied field, it is still an open problem, since a standard approach has yet to be found. In this notebook, we propose our model for the Authorship Attribution task of PAN 2019, that focuses on cross-domain setting covering 4 different languages: French, Italian, English, and Spanish. We use n-grams of characters, words, stemmed words, and distorted text. Our model has an SVM for each feature and an ensemble architecture. Our final results outperform the baseline given by PAN in almost every problem. With this model, we reach the second place in the task with an F1-score of 68%

    A Light in the Dark Web: Linking Dark Web aliases to real internet identities

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    Most users have several Internet names. On Facebook or LinkedIn, for example, people usually appear with the real one. On other standard websites, like forums, people often use aliases to protect their real identities with respect to the other users, with no real privacy against the web site and the authorities. Aliases in the Dark Web are different: users expect strong identity protection. In this paper, we show that using both “open” aliases (aliases used in the standard Web) and Dark Web aliases can be dangerous per se. Indeed, we develop tools to link Dark Web to open aliases. For the first time, we perform a massive scale experiment on real scenarios. First between two Dark Web forums, then between the Dark Web forums and the standard forums. Due to a large number of possible pairs, we first reduce the search space cutting down the number of potential matches to a small set of candidates, and then on the selection of the correct alias among these candidates. We show that our methodology has excellent precision, from 87% to 94%, and recall around 80%

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

    Bot and gender detection of twitter accounts using distortion and LSA notebook for PAN at CLEF 2019

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    In this work, we present our approach for the Author Profiling task of PAN 2019. The task is divided into two sub-problems, bot, and gender detection, for two different languages: English and Spanish. For each instance of the problem and each language, we address the problem differently. We use an ensemble architecture to solve the Bot Detection for accounts that write in English and a single SVM for those who write in Spanish. For the Gender detection we use a single SVM architecture for both the languages, but we pre-process the tweets in a different way. Our final models achieve accuracy over the 90% in the bot detection task, while for the gender detection, of 84.17% and 77.61% respectively for the English and Spanish languages

    Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: Review, challenges, and a case study

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    Big data stream mobile computing is proposed as a paradigm that relies on the convergence of broadband Internet mobile networking and real-time mobile cloud computing. It aims at fostering the rise of novel self-configuring integrated computing-communication platforms for enabling in real time the offloading and processing of big data streams acquired by resource-limited mobile/wireless devices. This position article formalizes this paradigm, discusses its most significant application opportunities, and outlines the major challenges in performing real-time energy-efficient management of the distributed resources available at both mobile devices and Internet-connected data centers. The performance analysis of a small-scale prototype is also included in order to provide insight into the energy vs. performance tradeoff that is achievable through the optimized design of the resource management modules. Performance comparisons with some state-of-the-art resource managers corroborate the discussion. Hints for future research directions conclude the article

    Variations on the Author

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    “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

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    We 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

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    We 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
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