BANKSAFE: Visual analytics for big data in large-scale computer networks

Fischer, Fabian; Fuchs, Johannes; Mansmann, Florian; Keim, Daniel A.

doi:10.1177/1473871613488572

Cited by 18 publications

(6 citation statements)

References 19 publications

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“…Fischer et al [147][148] introduce the BANKSAFE, a situational awareness application for large-scale computer networks that explores big data technologies and provides several visualization modules. Briefly, BANKSAFE gathers monitoring data, and security datasets stored in Google's BigQuery database service and provides a web-based interface to display different visualization modules.…”

Section: B State Of the Artmentioning

confidence: 99%

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A Survey on Information Visualization for Network and Service Management

Guimaraes

Freitas

Sadre

et al. 2016

IEEE Commun. Surv. Tutorials

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Network and service management encompasses a set of activities, methods, procedures, and tools whose ultimate goal is to guarantee the proper functioning of a networked system. Computational tools are essential to help network administrators in their daily tasks, and information visualization techniques are of great value in such context. In essence, information visualization techniques associated to visual analytics aim at facilitating the tasks of network administrators in the process of monitoring and maintaining the network health. This paper surveys the use of information visualization techniques as a tool to support the network and service management process. Through a Systematic Literature Review (SLR), we provide a historical overview and discuss the current state of the art in the field. We present a classification of 285 articles and papers from 1985 to 2013, according to an information visualization taxonomy as well as a network and service management taxonomy. Finally, we point out future research directions and opportunities regarding the use of information visualization in network and service management.Taking into account the example mentioned above, [15] and [17] are examples of articles/papers that match with the research goal. Thus, they are stored and cataloged, and their references are verified. In the analysis of the references of [15], for example, we found the work of Koike et al. "Visualizing cyber attacks using IP matrix" [19]. On the other hand, [16] is an example of a work that was discarded after the analysis of the abstract and keywords (i.e., the second step of filtering).Once finished the search process, a set of 374 articles and papers remained selected. These publications are from a time interval ranging from 1985 to 2013.

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Section: B State Of the Artmentioning

confidence: 99%

“…Fischer et al [147], in a very interesting work, share experiences on how to apply big data technology in a visual analytics application, more precisely, a network security application. We believe that there are several research opportunities in this field, beyond the security management.…”

Section: B Big Datamentioning

confidence: 99%

A Survey on Information Visualization for Network and Service Management

Guimaraes

Freitas

Sadre

et al. 2016

IEEE Commun. Surv. Tutorials

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“…Quite a few studies concentrate on solutions that give the user more freedom to visually represent information, rather than standard solutions, for which the structure of the visualization is fixed. Still other researchers address the challenge of visual analytics for big data with the enormous growth of data in the last few decades [41,42]. "GIS" continuously appears during 2004-2015.…”

Section: Identifying Research Trends With Network Analysismentioning

confidence: 99%

Using Text Mining Techniques to Identify Research Trends: A Case Study of Design Research

Nie

Sun

2017

Applied Sciences

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Abstract:The research goal of this paper is to identify major academic branches and to detect research trends in design research using text mining techniques. In this paper, the information about scientific literature in design research isprocessed. A combination of clustering and bibliometric analysis led to shaping four academic branches and summarizing each academic branch. Then, research trends and the evolution for each academic branch are explored. We perform a two-dimensional text mining approach, including bibliometric and network analysis, in order to detect trends of major academic branches. Specifically, the bibliometric characterization aims to assess design research area outputs, while the network analysis intends to reveal research trends in each academic branch of design research and the evolution of core research themes.

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“…BDA is identified among the key technologies that enable such cognitive smart systems [11]. Visual analytics (VA) of big data could be regarded as a pillar to this type of interaction, since it combines principles from HCI, advanced analytics and visualization [48][49][50]. The second representation is seen through interaction among users in social and collaborative services.…”

Section: The Servicementioning

confidence: 99%