The growth and evolution of threats, vulnerabilities and cyber-attacks increase security incidents and generate negative impacts on organizations. We present an online analytical processing (OLAP) system for early ale...
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ISBN:
(纸本)9781510838277
The growth and evolution of threats, vulnerabilities and cyber-attacks increase security incidents and generate negative impacts on organizations. We present an online analytical processing (OLAP) system for early alerts of upcoming malicious activities. This study aims to systematize the support of cybersecurity granted by a Computer Security Incident Response Team (CSIRT) and shall help to establish a mechanism to analyze and improve the overall level of security of networks and equipment by providing early warning services. In order to accomplish this task, a Business Intelligence solution has been developed adapting the methodology of Ralph Kimball to support the analysis of computer security incidents. This generates a data warehouse of information collected from alerts and events recorded from a continuous transmission of data from various Internet security sources that gather, trace and report malware, botnet, and electronic fraud. Furthermore, we constructed with Pentaho BI load data into the dimensions, measures and facts, OLAP cubes, reports and dashboards. The acquired results demonstrate the functionality of the application where it is possible to visualize with certainty of both, the early warnings, as well as the level of security of the participant Institutions, about the registered threats and vulnerabilities.
The growth and evolution of threats, vulnerabilities and cyber-attacks increase security incidents and generate negative impacts on organizations. We present an online analytical processing (OLAP) system for early ale...
详细信息
ISBN:
(纸本)9781510838277
The growth and evolution of threats, vulnerabilities and cyber-attacks increase security incidents and generate negative impacts on organizations. We present an online analytical processing (OLAP) system for early alerts of upcoming malicious activities. This study aims to systematize the support of cybersecurity granted by a Computer Security Incident Response Team (CSIRT) and shall help to establish a mechanism to analyze and improve the overall level of security of networks and equipment by providing early warning services. In order to accomplish this task, a Business Intelligence solution has been developed adapting the methodology of Ralph Kimball to support the analysis of computer security incidents. This generates a data warehouse of information collected from alerts and events recorded from a continuous transmission of data from various Internet security sources that gather, trace and report malware, botnet, and electronic fraud. Furthermore, we constructed with Pentaho BI load data into the dimensions, measures and facts, OLAP cubes, reports and dashboards. The acquired results demonstrate the functionality of the application where it is possible to visualize with certainty of both, the early warnings, as well as the level of security of the participant Institutions, about the registered threats and vulnerabilities.
P>1. Plant traits are fundamental for understanding and predicting vegetation responses to global changes, and they provide a promising basis towards a more quantitative and predictive approach to ecology. As a con...
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P>1. Plant traits are fundamental for understanding and predicting vegetation responses to global changes, and they provide a promising basis towards a more quantitative and predictive approach to ecology. As a consequence, information on plant traits is rapidly accumulating, and there is a growing need for efficient database tools that enable the assembly and synthesis of trait data. 2. Plant traits are highly heterogeneous, exhibit a low degree of standardization and are linked and interdependent at various levels of biological organization: tissue, organ, plant and population. Therefore, they often require ancillary data for interpretation, including descriptors of the biotic and abiotic environment, methods and taxonomic relationships. 3. We introduce a generic database structure that is tailored to accommodate plant trait complexity and is consistent with current theoretical approaches to characterize the structure of observational data. The over-arching utility of the proposed database structure is illustrated based on two independent plant trait database projects. 4. The generic database structure proposed here is meant to serve as a flexible blueprint for future plant trait databases, improving data discovery, and ensuring compatibility among them.
Aggregation is a key technique to enhance query response time in a large data warehouse. This paper analyzes its effects on query performance and memory requirements. A grocery shop data warehouse has been designed fo...
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ISBN:
(纸本)9781479929955
Aggregation is a key technique to enhance query response time in a large data warehouse. This paper analyzes its effects on query performance and memory requirements. A grocery shop data warehouse has been designed for simulation purpose using Red Gate data Generator tool along with the Business Intelligence Development Studio of Microsoft SQL Server2008. For a desired performance gain, the requirements on aggregate and its impact on memory usage has been studied. The effects of variation in size of base cube of a data Warehouse on memory requirement and performance gain have also been analyzed.
In this paper, the use of an evolutionary approach when obtaining linguistic summaries from time series data is proposed. We assume the availability of a hierarchical partition of the time dimension in the time series...
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ISBN:
(纸本)9789078677000
In this paper, the use of an evolutionary approach when obtaining linguistic summaries from time series data is proposed. We assume the availability of a hierarchical partition of the time dimension in the time series. The use of natural language allows the human users to understand the resulting summaries in an easy way. The number of possible final summaries and the different ways of measuring their quality has taken us to adopt the use of a multi objective evolutionary algorithm. We compare the results of the new approach with our previous greedy algorithms.
data cubes and OLAP (OnLine Analytical Processing) allow friendly ad-hoc data analysis in the process of decision making. Among the dimensions that describe the data cube structure, we usually find a time dimension. I...
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ISBN:
(纸本)9783642049569
data cubes and OLAP (OnLine Analytical Processing) allow friendly ad-hoc data analysis in the process of decision making. Among the dimensions that describe the data cube structure, we usually find a time dimension. If we query the data cube by means of OLAP operations on the time dimension we obtain time series data related to events and features which are interesting for the user. These query results can be summarized so that an appropriate short linguistic description of the series is provided to the user. In this paper, we present some approaches to accomplish linguistic summarization of data in data cubes containing historical information using fuzzy quantified statements.
data Cubes are the basic structure of the Multi-dimensional data model. OnLine Analytical Processing techniques together with data cubes come to overcome the limitation of conventional database models whose structures...
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ISBN:
(纸本)9783642043932
data Cubes are the basic structure of the Multi-dimensional data model. OnLine Analytical Processing techniques together with data cubes come to overcome the limitation of conventional database models whose structures are not well suited for the friendly ad-hoc analysis and display of large amounts of data decision support systems need. One of the dimensions that usually appears in data cubes is the time dimensions. The use of OnLine Analytical Processing operations through this dimension produces its result time series data that, ask for suitable summarization techniques in order to effectively present the information to the interested user. Soft Computing approaches to data summarization are widely used to carry out this task. In this paper, we introduce ail approach to linguistic summarization of data in data cubes with time dimension using frizzy quantified statements. Our approach uses as basis a time dimension defined by the user as a hierarchical collection of fuzzy time periods.
This study shows to what extent it is possible to use heuristics to distribute a set of dimensions defining a data point along the axes of a matrix. Matrices designed in this manner guarantee conceptual integrity betw...
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This study shows to what extent it is possible to use heuristics to distribute a set of dimensions defining a data point along the axes of a matrix. Matrices designed in this manner guarantee conceptual integrity between, on the one hand, the dimensional data model which defines semantics of and business rules applicable to data points, and on the other hand matrices presenting those data points. The data Point Methodology is used by the European Banking Authority (EBA) to specify data requirements. The result, a data point model, consists of a dimensional data model with data points, and matrices made by hand presenting those data points. A data point is defined by a set of dimensions, and one metric. The metric is merely a data type. One dimension carries the meaning of the metric. Checking whether the metric dimension is on the X-axis is a useful heuristic to review handmade matrices. We found examples of an additional metric dimension. Is one dimension to carry the meaning of the metric not enough? Further investigation needs to establish whether dimensional data modelling techniques need to improve their capability to represent the quantitative aspects of a fact.
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