Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm
Host-based Intrusion Detection System (IDS) utilizes the log files as the data source and is limited by the content of the log files. If the log files were tampered, the IDS cannot accurately detect illegal behaviors. Therefore, the proposed IDS for this paper will create its own data source file. T...
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| creator | Chen, Rongchang Chen, Jeanne Chen, Tungshou Hsieh, Chunhung Chen, Teyu Wu, Kaiyang |
| description | Host-based Intrusion Detection System (IDS) utilizes the log files as the data source and is limited by the content of the log files. If the log files were tampered, the IDS cannot accurately detect illegal behaviors. Therefore, the proposed IDS for this paper will create its own data source file. The system is controlled by the Client program and Server program. The client program is responsible for recording a user’s behavior in the data source file. The data source file is then transmitted to the server program, which will send it to SVM to be analyzed. The analyzed result will then be transmitted back to the client program. The client program will then decide on the course of actions to take based on the analyzed result. Also, the genetic algorithm is used to optimize information to extract from the data source file so that detection time can be optimized. |
| doi_str_mv | 10.1007/11427469_66 |
| format | Conference Proceeding |
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Also, the genetic algorithm is used to optimize information to extract from the data source file so that detection time can be optimized.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540259147</isbn><isbn>9783540259145</isbn><isbn>9783540259121</isbn><isbn>3540259120</isbn><isbn>3540320695</isbn><isbn>9783540320692</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNkDtPwzAQx81LopROfAEvDAwB--zY8dgHlEpFDDwmpMh1nNaQOpHtDv32pCoDt9zj97-T7o_QDSX3lBD5QCkHyYUqhThBVyznhAERKj9FAyoozRjj6uwIIFeUy3M0IIxApiRnl2gU4zfpg1HRTwfoa7JzTeX8GmuPFz6FXXStxzObrEmH6m0fk93iiY62wod-13VtSPiz523AL9psnLf9doXn1tvkDB436za4tNleo4taN9GO_vIQfTw9vk-fs-XrfDEdL7MOqEpZDXpV5aYgsgKaS74yooaCWqW4MgCcFlaD7H-xplDMWiAcOIdKVxYYETkbotvj3U5Ho5s6aG9cLLvgtjrsSyqKAkQhe93dURd75Nc2lKu2_YklJeXB2_Kft-wXnEtl-w</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Chen, Rongchang</creator><creator>Chen, Jeanne</creator><creator>Chen, Tungshou</creator><creator>Hsieh, Chunhung</creator><creator>Chen, Teyu</creator><creator>Wu, Kaiyang</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2005</creationdate><title>Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm</title><author>Chen, Rongchang ; Chen, Jeanne ; Chen, Tungshou ; Hsieh, Chunhung ; Chen, Teyu ; Wu, Kaiyang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p219t-f2abd5c807d21574bc6f281e9949c22418ea27914ec893ee2042442dade230653</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Learning and adaptive systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Rongchang</creatorcontrib><creatorcontrib>Chen, Jeanne</creatorcontrib><creatorcontrib>Chen, Tungshou</creatorcontrib><creatorcontrib>Hsieh, Chunhung</creatorcontrib><creatorcontrib>Chen, Teyu</creatorcontrib><creatorcontrib>Wu, Kaiyang</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Rongchang</au><au>Chen, Jeanne</au><au>Chen, Tungshou</au><au>Hsieh, Chunhung</au><au>Chen, Teyu</au><au>Wu, Kaiyang</au><au>Yi, Zhang</au><au>Liao, Xiao-Feng</au><au>Wang, Jun</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm</atitle><btitle>Advances in Neural Networks – ISNN 2005</btitle><date>2005</date><risdate>2005</risdate><spage>409</spage><epage>414</epage><pages>409-414</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540259147</isbn><isbn>9783540259145</isbn><isbn>9783540259121</isbn><isbn>3540259120</isbn><eisbn>3540320695</eisbn><eisbn>9783540320692</eisbn><abstract>Host-based Intrusion Detection System (IDS) utilizes the log files as the data source and is limited by the content of the log files. 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| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Advances in Neural Networks – ISNN 2005, 2005, p.409-414 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_16882687 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Learning and adaptive systems |
| title | Building an Intrusion Detection System Based on Support Vector Machine and Genetic Algorithm |
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