Intrusion detection method based on machine learning
A new intrusion detection method was presented based on machine learning for intrusion detection systems using shell commands as audit data.In the method,multiple dictionaries of shell command sequences of different lengths were constructed to represent the normal behavior profile of a network user....
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2006-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74663726/ |
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| _version_ | 1841537337630130176 |
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| author | TIAN Xin-guang1 GAO Li-zhi2 ZHANG Er-yang1 |
| author_facet | TIAN Xin-guang1 GAO Li-zhi2 ZHANG Er-yang1 |
| author_sort | TIAN Xin-guang1 |
| collection | DOAJ |
| description | A new intrusion detection method was presented based on machine learning for intrusion detection systems using shell commands as audit data.In the method,multiple dictionaries of shell command sequences of different lengths were constructed to represent the normal behavior profile of a network user.During the detection stage,the similarities between the command sequences generated by the monitored user and the sequence dictionaries were calculated.These similarities were then smoothed with sliding windows,and the smoothed similarities were used to determine whether the monitored user’s behaviors were normal or anomalous.The results of the experience show the method can achieve higher detection accuracy and shorter detection time than the instance-based method presented by Lane T. |
| format | Article |
| id | doaj-art-146574e5372b402fb66adeefc9070059 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2006-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-146574e5372b402fb66adeefc90700592025-01-14T08:39:16ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2006-01-0110811474663726Intrusion detection method based on machine learningTIAN Xin-guang1GAO Li-zhi2ZHANG Er-yang1A new intrusion detection method was presented based on machine learning for intrusion detection systems using shell commands as audit data.In the method,multiple dictionaries of shell command sequences of different lengths were constructed to represent the normal behavior profile of a network user.During the detection stage,the similarities between the command sequences generated by the monitored user and the sequence dictionaries were calculated.These similarities were then smoothed with sliding windows,and the smoothed similarities were used to determine whether the monitored user’s behaviors were normal or anomalous.The results of the experience show the method can achieve higher detection accuracy and shorter detection time than the instance-based method presented by Lane T.http://www.joconline.com.cn/zh/article/74663726/information processing techniqueintrusion detectionmachine learningbehavioral pattern |
| spellingShingle | TIAN Xin-guang1 GAO Li-zhi2 ZHANG Er-yang1 Intrusion detection method based on machine learning Tongxin xuebao information processing technique intrusion detection machine learning behavioral pattern |
| title | Intrusion detection method based on machine learning |
| title_full | Intrusion detection method based on machine learning |
| title_fullStr | Intrusion detection method based on machine learning |
| title_full_unstemmed | Intrusion detection method based on machine learning |
| title_short | Intrusion detection method based on machine learning |
| title_sort | intrusion detection method based on machine learning |
| topic | information processing technique intrusion detection machine learning behavioral pattern |
| url | http://www.joconline.com.cn/zh/article/74663726/ |
| work_keys_str_mv | AT tianxinguang1 intrusiondetectionmethodbasedonmachinelearning AT gaolizhi2 intrusiondetectionmethodbasedonmachinelearning AT zhangeryang1 intrusiondetectionmethodbasedonmachinelearning |