1,720,954 research outputs found
Analisis Big Data untuk Keamanan Siber
No full textThe era of the Internet of Things with billions of connected devices has created an increasingly large surface for cyber attackers to exploit, resulting in the need for faster, up-to-date and accurate detection of such attacks. In the last few years the growth of data in volume, correctness, speed, and variation of data is extremely fast. When large data sets or better known as Big Data are collected from or generated by different devices and sources, intelligent big data analysis techniques are required to mine, interpret and visualize the data. In terms of information system security, there is no protection that can guarantee that there will be no attacks or cyber simulation actions against a company or organization. Moreover, the laws governing the protection of personal data GDPR (General Data Protection Regulation), especially in Indonesia, have not been thoroughly discussed by regulators, so the use of automated tools is combined with a security operations center consisting of experts and collaborating with global threats. intelligence is the most up-to-date collaborative method as a precautionary measure and right now to be more proactive and also very useful for preventing cyber attacks. The purpose of this research is to provide knowledge and understanding of the strengths and the importance of using automated tools or collaborating with security operations centers that have international standards in managing event logs of all IT devices owned within a company or organization so that information security systems, especially vulnerabilities from a tool can be detected early, especially regarding data leakage can be minimized.Dalam beberapa tahun terakhir ini pertumbuhan data dalam volume, kebenaran, kecepatan, dan variasi data luar biasa cepat. Ketika sejumlah besar data dikumpulkan dari atau dihasilkan oleh perangkat dan sumber yang berbeda, teknik analisis data besar yang cerdas diperlukan untuk menambang, menafsirkan, dan memvisualisasikan data tersebut. Dalam pertahanan keamanan sistem informasi tidak ada yang bisa menjamin bahwa tidak akan ada serangan ataupun melakukan simulasi siber ke dalam suatu perusahaan atau organisasi. Tujuan dari penelitian ini yaitu memberikan wawasan tentang pentingnya penggunaan alat bantu atau pusat operasi keamanan untuk mengolah log event dari semua perangkat IT yang dimiliki di dalam suatu perusahaan atau organisasi agar sistem keamanan informasi terutama mengenai kebocoran data dapat diminimalisir
Analisis Big Data untuk Keamanan Siber
No full textThe era of the Internet of Things with billions of connected devices has created an increasingly large surface for cyber attackers to exploit, resulting in the need for faster, up-to-date and accurate detection of such attacks. In the last few years the growth of data in volume, correctness, speed, and variation of data is extremely fast. When large data sets or better known as Big Data are collected from or generated by different devices and sources, intelligent big data analysis techniques are required to mine, interpret and visualize the data. In terms of information system security, there is no protection that can guarantee that there will be no attacks or cyber simulation actions against a company or organization. Moreover, the laws governing the protection of personal data GDPR (General Data Protection Regulation), especially in Indonesia, have not been thoroughly discussed by regulators, so the use of automated tools is combined with a security operations center consisting of experts and collaborating with global threats. intelligence is the most up-to-date collaborative method as a precautionary measure and right now to be more proactive and also very useful for preventing cyber attacks. The purpose of this research is to provide knowledge and understanding of the strengths and the importance of using automated tools or collaborating with security operations centers that have international standards in managing event logs of all IT devices owned within a company or organization so that information security systems, especially vulnerabilities from a tool can be detected early, especially regarding data leakage can be minimized.Dalam beberapa tahun terakhir ini pertumbuhan data dalam volume, kebenaran, kecepatan, dan variasi data luar biasa cepat. Ketika sejumlah besar data dikumpulkan dari atau dihasilkan oleh perangkat dan sumber yang berbeda, teknik analisis data besar yang cerdas diperlukan untuk menambang, menafsirkan, dan memvisualisasikan data tersebut. Dalam pertahanan keamanan sistem informasi tidak ada yang bisa menjamin bahwa tidak akan ada serangan ataupun melakukan simulasi siber ke dalam suatu perusahaan atau organisasi. Tujuan dari penelitian ini yaitu memberikan wawasan tentang pentingnya penggunaan alat bantu atau pusat operasi keamanan untuk mengolah log event dari semua perangkat IT yang dimiliki di dalam suatu perusahaan atau organisasi agar sistem keamanan informasi terutama mengenai kebocoran data dapat diminimalisir
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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