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Implementation of Regular Expression Grouping in MapReduce Paradigm
Šafář, Martin ; Dvořák, Milan (referee) ; Kaštil, Jan (advisor)
The greatest contribution of this thesis is design and implementation of program, that uses MapReduce paradigm and Apache Hadoop for acceleration of regular expression grouping. This paper also describes algorithms, that are used for regular expression grouping and proposes some improvements for these algorithms. Experiments carried out in this thesis show, that a cluster of 20 computers can speed up the grouping ten times.
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Automatic Grouping of Regular Expressions
Stanek, Timotej ; Kořenek, Jan (referee) ; Kaštil, Jan (advisor)
This project is about security of computer networks using Intrusion Detection Systems. IDS contain rules for detection expressed with regular expressions, which are for detection represented by finite-state automata. The complexity of this detection with non-deterministic and deterministic finite-state automata is explained. This complexity can be reduced with help of regular expressions grouping. Grouping algorithm and approaches for speedup and improvement are introduced. One of the approches is Genetic algorithm, which can work real-time. Finally Random search algorithm for grouping of regular expressions is presented. Experiment results with these approches are shown and compared between each other.
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Implementation of Regular Expression Grouping in MapReduce Paradigm
Šafář, Martin ; Dvořák, Milan (referee) ; Kaštil, Jan (advisor)
The greatest contribution of this thesis is design and implementation of program, that uses MapReduce paradigm and Apache Hadoop for acceleration of regular expression grouping. This paper also describes algorithms, that are used for regular expression grouping and proposes some improvements for these algorithms. Experiments carried out in this thesis show, that a cluster of 20 computers can speed up the grouping ten times.
|
|
|
Automatic Grouping of Regular Expressions
Stanek, Timotej ; Kořenek, Jan (referee) ; Kaštil, Jan (advisor)
This project is about security of computer networks using Intrusion Detection Systems. IDS contain rules for detection expressed with regular expressions, which are for detection represented by finite-state automata. The complexity of this detection with non-deterministic and deterministic finite-state automata is explained. This complexity can be reduced with help of regular expressions grouping. Grouping algorithm and approaches for speedup and improvement are introduced. One of the approches is Genetic algorithm, which can work real-time. Finally Random search algorithm for grouping of regular expressions is presented. Experiment results with these approches are shown and compared between each other.
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