A Deviation Based Outlier Intrusion Detection System
With the significant increase in use of networks, network security has become more important and challenging. An intrusion detection system plays a major role in providing security. This paper proposes a model in which Artificial Neural Network and Data Mining approaches are used together. In this m...
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          | Published in | Recent Trends in Network Security and Applications pp. 395 - 401 | 
|---|---|
| Main Authors | , , , , | 
| Format | Book Chapter | 
| Language | English | 
| Published | 
        Berlin, Heidelberg
          Springer Berlin Heidelberg
    
        2010
     | 
| Series | Communications in Computer and Information Science | 
| Subjects | |
| Online Access | Get full text | 
| ISBN | 9783642144776 3642144772  | 
| ISSN | 1865-0929 1865-0937  | 
| DOI | 10.1007/978-3-642-14478-3_39 | 
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| Abstract | With the significant increase in use of networks, network security has become more important and challenging. An intrusion detection system plays a major role in providing security. This paper proposes a model in which Artificial Neural Network and Data Mining approaches are used together. In this model “Self Organizing Map” approach is used for behavior learning and “Outlier Mining” approach is used for detecting an intruder. The scope of the proposed model is for internet. This model improves the capability of detecting intruders: both masqueraders and misfeasors. | 
    
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| AbstractList | With the significant increase in use of networks, network security has become more important and challenging. An intrusion detection system plays a major role in providing security. This paper proposes a model in which Artificial Neural Network and Data Mining approaches are used together. In this model “Self Organizing Map” approach is used for behavior learning and “Outlier Mining” approach is used for detecting an intruder. The scope of the proposed model is for internet. This model improves the capability of detecting intruders: both masqueraders and misfeasors. | 
    
| Author | Bansal, Shruti Mishra, Aditi Sharma, Arpana Pareek, Vikas Chauhan, Rashmi  | 
    
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| Editor | Nagamalai, Dhinaharan Boumerdassi, Selma Meghanathan, Natarajan Chaki, Nabendu  | 
    
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| PublicationSubtitle | Third International Conference, CNSA 2010, Chennai, India, July 23-25, 2010. Proceedings | 
    
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| SubjectTerms | Artificial Neural Network Data mining Internet Intrusion Detection Network Security  | 
    
| Title | A Deviation Based Outlier Intrusion Detection System | 
    
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