Applying correlation analysis methods to control flow violation detection in the internet of things

Lavrova, Daria S.; Pechenkin, Alexander I.; Gluhov, Vladimir

doi:10.3103/s0146411615080283

Cited by 33 publications

(4 citation statements)

References 2 publications

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“…There are in the literature some authors who propose applying geostatistics in the IoT environment in many different ways [35][36][37]. However, these works do not demonstrate the application method with concrete results, and they also do not propose a systematic way to apply the techniques-some of them only discuss the potential.…”

Section: Spatial Autocorrelationmentioning

confidence: 99%

Analysis of Spatially Distributed Data in Internet of Things in the Environmental Context

Azevedo

Estrella

Delbem

et al. 2022

Sensors

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The Internet of Things consists of “things” made up of small sensors and actuators capable of interacting with the environment. The combination of devices with sensor networks and Internet access enables the communication between the physical world and cyberspace, enabling the development of solutions to many real-world problems. However, most existing applications are dedicated to solving a specific problem using only private sensor networks, which limits the actual capacity of the Internet of Things. In addition, these applications are concerned with the quality of service offered by the sensor network or the correct analysis method that can lead to inaccurate or irrelevant conclusions, which can cause significant harm for decision makers. In this context, we propose two systematic methods to analyze spatially distributed data Internet of Things. We show with the results that geostatistics and spatial statistics are more appropriate than classical statistics to do this analysis.

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Section: Spatial Autocorrelationmentioning

confidence: 99%

Analysis of Spatially Distributed Data in Internet of Things in the Environmental Context

Azevedo

Estrella

Delbem

et al. 2022

Sensors

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“…We also aim to guarantee scalability. Indeed, having a fairly large number of users and communication channels is a scenario that will soon happen with the emergence of IoT (Internet of things) [27]. It should also be noted that CR is a promising enabler communication technology for IoT [28].…”

Section: Our Implementation Of Parallel Dynamic Programming On a Mult...mentioning

confidence: 99%

A parallel implementation on a multi-core architecture of a dynamic programming algorithm applied in cognitive radio ad hoc networks

Benmammar¹,

Benmouna²,

Amraoui³

et al. 2022

Int. j. commun. netw. inf. secur.

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Spectral resources allocation is a major problem in cognitive radio ad hoc networks and currently most of the research papers use meta-heuristics to solve it. On the other side, the term parallelism refers to techniques to make programs faster by performing several computations in parallel. Parallelism would be very interesting to increase the performance of real-time systems, especially for the cognitive radio ad hoc networks that interest us in this work. In this paper, we present a parallel implementation on a multi-core architecture of dynamic programming algorithm applied in cognitive radio ad hoc networks. Our simulations approve the desired results, showing significant gain in terms of execution time. The main objective is to allow a cognitive engine to use an exact method and to have better results compared to the use of meta-heuristics.

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“…It may also require a large database of templates to identify a polymorphic intrusion, for which the indicative variants of its exploitation are different. The use of more complex, for instance, heuristic, signature-based methods allows the use of logical rules to set threshold values of monitored parameters, the excess of which indicates a violation [8,9]. Then, with precise definition of the detection rules, intrusion detection faults are minimized.…”

Section: The Sequence Alignment Algorithmsmentioning

confidence: 99%

Sequence Alignment Algorithms for Intrusion Detection in the Internet of Things

Kalinin

Krundyshev

2020

Nonlinear Phenomena in Complex Systems

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The paper reviews the intrusion detection approach based on bioinformatics algorithms for alignment and comparing of the nucleotide sequences. Sequence alignment is a natureclose computational procedure for matching the coded strings by searching for the regions of individual characteristics that are located in the same order. A calculated rank of similarity is used instead of equity checking to estimate the distance between a sequence of the monitored operational acts and a generalized intrusion pattern. Multiple alignment schema is more effective and accurate than the Smith–Waterman local alignment due to ability to find few blocks of similarity. In comparison with a traditional signature-based IDS, it is found that the nature-inspired approach provides the better work characteristics. The experimental study have shown that new approach demonstrates high, 99 percent, level of accuracy.

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Applying correlation analysis methods to control flow violation detection in the internet of things

Cited by 33 publications

References 2 publications

Analysis of Spatially Distributed Data in Internet of Things in the Environmental Context

Analysis of Spatially Distributed Data in Internet of Things in the Environmental Context

A parallel implementation on a multi-core architecture of a dynamic programming algorithm applied in cognitive radio ad hoc networks

Sequence Alignment Algorithms for Intrusion Detection in the Internet of Things

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