The Use of Template Miners and Encryption in Log Message Compression
Presently, almost every computer software produces many log messages based on events and activities during the usage of the software. These files contain valuable runtime information that can be used in a variety of applications such as anomaly detection, error prediction, template mining, and so on...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Computers |
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| Online Access: | https://www.mdpi.com/2073-431X/10/7/83 |
| _version_ | 1827689014541418496 |
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| author | Péter Marjai Péter Lehotay-Kéry Attila Kiss |
| author_facet | Péter Marjai Péter Lehotay-Kéry Attila Kiss |
| author_sort | Péter Marjai |
| collection | DOAJ |
| description | Presently, almost every computer software produces many log messages based on events and activities during the usage of the software. These files contain valuable runtime information that can be used in a variety of applications such as anomaly detection, error prediction, template mining, and so on. Usually, the generated log messages are raw, which means they have an unstructured format. This indicates that these messages have to be parsed before data mining models can be applied. After parsing, template miners can be applied on the data to retrieve the events occurring in the log file. These events are made from two parts, the template, which is the fixed part and is the same for all instances of the same event type, and the parameter part, which varies for all the instances. To decrease the size of the log messages, we use the mined templates to build a dictionary for the events, and only store the dictionary, the event ID, and the parameter list. We use six template miners to acquire the templates namely IPLoM, LenMa, LogMine, Spell, Drain, and MoLFI. In this paper, we evaluate the compression capacity of our dictionary method with the use of these algorithms. Since parameters could be sensitive information, we also encrypt the files after compression and measure the changes in file size. We also examine the speed of the log miner algorithms. Based on our experiments, LenMa has the best compression rate with an average of 67.4%; however, because of its high runtime, we would suggest the combination of our dictionary method with IPLoM and FFX, since it is the fastest of all methods, and it has a 57.7% compression rate. |
| first_indexed | 2024-03-10T10:07:41Z |
| format | Article |
| id | doaj.art-9941e9308e99466ea59ece28d883de0a |
| institution | Directory Open Access Journal |
| issn | 2073-431X |
| language | English |
| last_indexed | 2024-03-10T10:07:41Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj.art-9941e9308e99466ea59ece28d883de0a2023-11-22T01:24:01ZengMDPI AGComputers2073-431X2021-06-011078310.3390/computers10070083The Use of Template Miners and Encryption in Log Message CompressionPéter Marjai0Péter Lehotay-Kéry1Attila Kiss2Department of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, HungaryDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, HungaryDepartment of Information Systems, ELTE Eötvös Loránd University, 1117 Budapest, HungaryPresently, almost every computer software produces many log messages based on events and activities during the usage of the software. These files contain valuable runtime information that can be used in a variety of applications such as anomaly detection, error prediction, template mining, and so on. Usually, the generated log messages are raw, which means they have an unstructured format. This indicates that these messages have to be parsed before data mining models can be applied. After parsing, template miners can be applied on the data to retrieve the events occurring in the log file. These events are made from two parts, the template, which is the fixed part and is the same for all instances of the same event type, and the parameter part, which varies for all the instances. To decrease the size of the log messages, we use the mined templates to build a dictionary for the events, and only store the dictionary, the event ID, and the parameter list. We use six template miners to acquire the templates namely IPLoM, LenMa, LogMine, Spell, Drain, and MoLFI. In this paper, we evaluate the compression capacity of our dictionary method with the use of these algorithms. Since parameters could be sensitive information, we also encrypt the files after compression and measure the changes in file size. We also examine the speed of the log miner algorithms. Based on our experiments, LenMa has the best compression rate with an average of 67.4%; however, because of its high runtime, we would suggest the combination of our dictionary method with IPLoM and FFX, since it is the fastest of all methods, and it has a 57.7% compression rate.https://www.mdpi.com/2073-431X/10/7/83log file processingtemplate miningcompressionencryption |
| spellingShingle | Péter Marjai Péter Lehotay-Kéry Attila Kiss The Use of Template Miners and Encryption in Log Message Compression Computers log file processing template mining compression encryption |
| title | The Use of Template Miners and Encryption in Log Message Compression |
| title_full | The Use of Template Miners and Encryption in Log Message Compression |
| title_fullStr | The Use of Template Miners and Encryption in Log Message Compression |
| title_full_unstemmed | The Use of Template Miners and Encryption in Log Message Compression |
| title_short | The Use of Template Miners and Encryption in Log Message Compression |
| title_sort | use of template miners and encryption in log message compression |
| topic | log file processing template mining compression encryption |
| url | https://www.mdpi.com/2073-431X/10/7/83 |
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