Bat4CEP: a bat algorithm for mining of complex event processing rules

Bruns, Ralf; Dunkel, Jürgen

doi:10.1007/s10489-022-03256-2

Cited by 6 publications

(2 citation statements)

References 48 publications

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“…Can we generalize the derived conclusions? Are the results also valid in GP applications outside attribute grammars, such as Lisp programming [5,8], event processing rules [71], trading rules [72], and model-driven engineering artefacts [73]? To answer this research question, controlled experiments regarding the comprehension of GP solutions must be performed outside of attribute grammars.…”

Section: Threats To Validitymentioning

confidence: 99%

The Impact of Code Bloat on Genetic Program Comprehension: Replication of a Controlled Experiment on Semantic Inference

Kosar,

Kovačević,

Mernik

et al. 2023

Mathematics

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Our previous study showed that automatically generated attribute grammars were harder to comprehend than manually written attribute grammars, mostly due to unexpected solutions. This study is an internally differentiated replication of the previous experiment, but, unlike the previous one, it focused on testing the influence of code bloat on comprehension correctness and efficiency. While the experiment’s context, design, and measurements were kept mostly the same as in the original experiment, more realistic code bloat examples were introduced. The replicated experiment was conducted with undergraduate students from two universities, showing statistically significant differences in comprehension correctness and efficiency between attribute grammars without code bloat and attribute grammars with code bloat, although the participants perceived attribute grammars with code bloat as simple as attribute grammars without code bloat. On the other hand, there was no statistically significant difference in comprehension correctness and efficiency between automatically generated attribute grammars with possible unexpected solutions and attribute grammars with code bloat, although there was a statistically significant difference in participants’ perspective of simplicity between automatically generated attribute grammars with possible unexpected solutions and attribute grammars with code bloat. The participants perceived attribute grammars with code bloat as significantly simpler than automatically generated attribute grammars.

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Section: Threats To Validitymentioning

confidence: 99%

The Impact of Code Bloat on Genetic Program Comprehension: Replication of a Controlled Experiment on Semantic Inference

Kosar,

Kovačević,

Mernik

et al. 2023

Mathematics

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show abstract

“…In this group we find proposals that do not require prior rules, but label complex events based on historical data. One paper in this category is that of Bruns et al [23], which succeeds in adapting the bat algorithm to the CEP rule search by structuring the different CEP operators, attribute values and time windows in the form of a tree. In this way the algorithm determines these values in the rule they represent.…”

Section: Supervised Without Prior Rulesmentioning

confidence: 99%

An automatic unsupervised complex event processing rules generation architecture for real-time IoT attacks detection

et al. 2023

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In recent years, the Internet of Things (IoT) has grown rapidly, as has the number of attacks against it. Certain limitations of the paradigm, such as reduced processing capacity and limited main and secondary memory, make it necessary to develop new methods for detecting attacks in real time as it is difficulty to adapt as has the techniques used in other paradigms. In this paper, we propose an architecture capable of generating complex event processing (CEP) rules for real-time attack detection in an automatic and completely unsupervised manner. To this end, CEP technology, which makes it possible to analyze and correlate a large amount of data in real time and can be deployed in IoT environments, is integrated with principal component analysis (PCA), Gaussian mixture models (GMM) and the Mahalanobis distance. This architecture has been tested in two different experiments that simulate real attack scenarios in an IoT network. The results show that the rules generated achieved an F1 score of .9890 in detecting six different IoT attacks in real time.

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Multi-level CEP rules automatic extraction approach for air quality detection and energy conservation decision based on AI technologies

Liu,

Yu,

Zhai

et al. 2024

Applied Energy

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Bat4CEP: a bat algorithm for mining of complex event processing rules

Cited by 6 publications

References 48 publications

The Impact of Code Bloat on Genetic Program Comprehension: Replication of a Controlled Experiment on Semantic Inference

The Impact of Code Bloat on Genetic Program Comprehension: Replication of a Controlled Experiment on Semantic Inference

An automatic unsupervised complex event processing rules generation architecture for real-time IoT attacks detection

Multi-level CEP rules automatic extraction approach for air quality detection and energy conservation decision based on AI technologies

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