Security Analysis Based on Controlling Dependences of Network Traffic Parameters by Wavelet Transformation

Lavrova, Daria S.; Alekseev, I. V.; Shtyrkina, Anna A.

doi:10.3103/s0146411618080187

Cited by 20 publications

(6 citation statements)

References 3 publications

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“…Time series of data are used to analyze self-similar processes. The input data for intrusion detection systems are parameters extracted from traffic [2,8,9] or time series [2,3,7,10]. The data preparation system aggregates traffic statistics over a set of specified time periods.…”

Section: Data Aggregation When Analyzing Self-similar Processesmentioning

confidence: 99%

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Multi-Dimensional Data Aggregation in the Analysis of Self-Similar Processes

Poltavtseva

Andreeva

2020

Nonlinear Phenomena in Complex Systems

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Analyzing self-similar processes in various fields requires fast and efficient processing of large amounts of data. The frequency and time scalability of self-similar processes require analysis over multiple time periods. Thus it is necessary to develop effective methods of data aggregation. The paper considers the hierarchical organization of time series and multidimensional aggregation based on a graph. The effectiveness of the proposed aggregation methods and their applicability to the analysis of self-similar processes in various fields are evaluated.

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Section: Data Aggregation When Analyzing Self-similar Processesmentioning

confidence: 99%

“…For example, to detect traffic anomalies [1,2]. In this case, not only batch systems for processing big data using Map-Reduce technology are used [3]. For such tasks, one need to use streaming processing modules [4], including special Big data aggregation components [5].…”

Section: Introductionmentioning

confidence: 99%

Multi-Dimensional Data Aggregation in the Analysis of Self-Similar Processes

Poltavtseva

Andreeva

2020

Nonlinear Phenomena in Complex Systems

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“…These are network traffic [6][7][8] and physical node data [9,10]. Today, there are a large number of works aimed at analyzing network traffic in monitoring systems to solve various security problems [11][12][13]. Recently, this field has been dominated by works using streaming information processing technologies [14] or (earlier) combining streaming and batch technologies [6,15].…”

Section: Related Workmentioning

confidence: 99%

“…The combination of these data is used to detect anomalies by various methods in industrial cyberphysical systems [8][9][10]13]. The heterogeneity of the physical process sensors is an additional challenge.…”

Section: Data Preprocessing In the Cpsmentioning

confidence: 99%

Heterogeneous Data Aggregation and Normalization in Information Security Monitoring and Intrusion Detection Systems of Large-scale Industrial CPS

Poltavtseva¹

2020

Proceedings of ISP RAS

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Monitoring of industrial cyber-physical systems (CPS) is an ongoing process necessary to ensure their security. The effectiveness of information security monitoring depends on the quality and speed of collection, processing, and analyzing of heterogeneous CPS data. Today, there are many methods of analysis for solving security problems of distributed industrial CPS. These methods have different requirements for the input data characteristics, but there are common features in them due to the subject area. The work is devoted to preliminary data processing for the security monitoring of industrial CPS in modern conditions. The general architecture defines the use of aggregation and normalization methods for data preprocessing. The work includes the issue from the requirements for the preprocessing system, the specifics of the subject area, to the general architecture and specific methods of multidimensional data aggregation.

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“…is built on the basis of passive strategies, its effect is not desirable if the business process' security isn't regarded as not strengthening the business process, the operation system and the computer hosts, it only depends on the computer drills with the thread codes to achieve effect. Thus, it's important to evaluate the computer network security [49]- [53]. The evaluating problems of computer network security are a classical multiple attribute decision making (MADM) problems.…”

Section: Introductionmentioning

confidence: 99%

MADM Method With Interval-Valued Bipolar Uncertain Linguistic Information for Evaluating the Computer Network Security

Gao

Wei

et al. 2019

IEEE Access

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In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some interval-valued bipolar uncertain linguistic aggregating operators. Then, the good properties of these proposed operators are investigated and these operators are used to solve the interval-valued bipolar uncertain linguistic multiple attribute decision making (MADM) problems. An example for evaluating the computer network security is given to illustrate the proposed methodology. INDEX TERMS Multiple attribute decision making (MADM), bipolar fuzzy sets (BFSs), interval-valued bipolar uncertain linguistic sets (IVBULSs), interval-valued bipolar uncertain linguistic hybrid average (IVBULHA) operator, interval-valued bipolar uncertain linguistic hybrid geometric (IVBULHG) operator, computer network security.

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Security Analysis Based on Controlling Dependences of Network Traffic Parameters by Wavelet Transformation

Cited by 20 publications

References 3 publications

Multi-Dimensional Data Aggregation in the Analysis of Self-Similar Processes

Multi-Dimensional Data Aggregation in the Analysis of Self-Similar Processes

Heterogeneous Data Aggregation and Normalization in Information Security Monitoring and Intrusion Detection Systems of Large-scale Industrial CPS

MADM Method With Interval-Valued Bipolar Uncertain Linguistic Information for Evaluating the Computer Network Security

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