Botnet Detection Using Graphical Lasso with Graph Density

The usual approaches to describing and understanding ecological processes in a landscape use patch-mosaic models based on traditional landscape metrics. However, they do not consider that many of these processes cannot be observed without considering the multiple interactions between different land-use patches in the landscape. The objective of this research was to provide a synthetic overview of graph metrics that characterize landscapes based on patch-mosaic models and to analyze the ecological meaning of the metrics to propose a relevant selection explaining biodiversity patterns and ecological processes. First, we conducted a literature review of graph metrics applied in ecology. Second, a case study was used to explore the behavior of a group of selected graph metrics in actual differentiated landscapes located in a long-term socioecological research site in Brittany, France. Thirteen landscape-scale metrics and 10 local-scale metrics with ecological significance were analyzed. Metrics were grouped for landscape-scale and local-scale analysis. Many of the metrics were able to identify differences between the landscapes studied. Lastly, we discuss how graph metrics offer a new perspective for landscape analysis, describe the main characteristics related to their calculation and the type of information provided, and discuss their potential applications in different ecological contexts.

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Botnet Detection Using Graphical Lasso with Graph Density

Cited by 3 publications

References 5 publications

Real-Time Detection of Malware Activities by Analyzing Darknet Traffic Using Graphical Lasso

Real-Time Detection of Malware Activities by Analyzing Darknet Traffic Using Graphical Lasso

Automated Detection of Malware Activities Using Nonnegative Matrix Factorization

Selecting Graph Metrics with Ecological Significance for Deepening Landscape Characterization: Review and Applications

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