|
|
Design of S-Boxes Using Genetic Algorithms
Hovorka, Bedřich ; Zadina, Martin (referee) ; Hanáček, Petr (advisor)
This work deals with part of the encryption algorithm, called S-box and its development. For its development is used evolutionary computing, such as classical genetic algorithm, Estimation of Distribution Algorithm, Cartesian genetic programming and multi-criteria VEGA and SPEA algorithms. This thesis aims to test the properties of substitution boxes to its evolutionary development. Firstly, the work deals with cryptography and issues of s-boxes. There are explained basic concepts and describes the selected criteria of safety. Next chapter explains evolutionary algorithms and multi-criteria optimization. This knowledge is used to design and program implementation, which are described below. Finally discusses the application of the criteria studied. Discussed here is searching S-boxes in both single-criteria, and especially in multi-criteria genetic search.
|
|
|
Performance Monitoring of MES PHARIS
Ondráček, Aleš ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This diploma thesis deals with the performance monitoring of automated development processes and performance testing of the MES PHARIS system. The main scope of thesis is the collection of data on tasks performed on automation servers DevOps and Jenkins, processing of this data and their subsequent visualization. The second part of the diploma thesis deals with the processing of data from performance testing and their appropriate representation using visualization. The core technology that is used is ELK Stack.
|
|
|
Implementation of an evolutionary expert system
Bukáček, Jan ; Müller, Jakub (referee) ; Karásek, Jan (advisor)
This thesis is focused on working up evolutionals and genetics algorithms issues Especially for multiobjective algorithms VEGA, SPEA and NSGA – II. Thereinafter one of FrameWork working with genetics algorithms namely WWW NIMBUS. From this mentioned algorithms was selected VEGA algorithm for implementation in JAVA to preselected problem. Thereby problem is choice thick columns of profile according to predetermined criteria. Selected algorithm works on division of population into several groups and each group evaluates the resulting fitness function. Here is a sample implementation of this algorithm. Furthermore there is a example of working with FrameWork. In the next section are compared the results of generated progam with results that were obtained by FrameWork WWW NIMBUS. As for VEGA, and the Nimbus there are shown different results. The VEGA is presented also the development of individual fitness functions. Also, there are shown graphs, that can be obtained from NIMBUS. At the end of work is introduced the comparation of the results ane propose possible improvements.
|
|
|
Performance Monitoring of MES PHARIS
Ondráček, Aleš ; Hruška, Martin (referee) ; Smrčka, Aleš (advisor)
This diploma thesis deals with the performance monitoring of automated development processes and performance testing of the MES PHARIS system. The main scope of thesis is the collection of data on tasks performed on automation servers DevOps and Jenkins, processing of this data and their subsequent visualization. The second part of the diploma thesis deals with the processing of data from performance testing and their appropriate representation using visualization. The core technology that is used is ELK Stack.
|
|
|
Design of S-Boxes Using Genetic Algorithms
Hovorka, Bedřich ; Zadina, Martin (referee) ; Hanáček, Petr (advisor)
This work deals with part of the encryption algorithm, called S-box and its development. For its development is used evolutionary computing, such as classical genetic algorithm, Estimation of Distribution Algorithm, Cartesian genetic programming and multi-criteria VEGA and SPEA algorithms. This thesis aims to test the properties of substitution boxes to its evolutionary development. Firstly, the work deals with cryptography and issues of s-boxes. There are explained basic concepts and describes the selected criteria of safety. Next chapter explains evolutionary algorithms and multi-criteria optimization. This knowledge is used to design and program implementation, which are described below. Finally discusses the application of the criteria studied. Discussed here is searching S-boxes in both single-criteria, and especially in multi-criteria genetic search.
|
|
|
Implementation of an evolutionary expert system
Bukáček, Jan ; Müller, Jakub (referee) ; Karásek, Jan (advisor)
This thesis is focused on working up evolutionals and genetics algorithms issues Especially for multiobjective algorithms VEGA, SPEA and NSGA – II. Thereinafter one of FrameWork working with genetics algorithms namely WWW NIMBUS. From this mentioned algorithms was selected VEGA algorithm for implementation in JAVA to preselected problem. Thereby problem is choice thick columns of profile according to predetermined criteria. Selected algorithm works on division of population into several groups and each group evaluates the resulting fitness function. Here is a sample implementation of this algorithm. Furthermore there is a example of working with FrameWork. In the next section are compared the results of generated progam with results that were obtained by FrameWork WWW NIMBUS. As for VEGA, and the Nimbus there are shown different results. The VEGA is presented also the development of individual fitness functions. Also, there are shown graphs, that can be obtained from NIMBUS. At the end of work is introduced the comparation of the results ane propose possible improvements.
|
guest ::
