A survey of anomaly detection using data mining methods for hypertext transfer protocol web services
In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic too...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Science Publications
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/43614/ http://psasir.upm.edu.my/id/eprint/43614/1/A%20survey%20of%20anomaly%20detection%20using%20data%20mining%20methods%20for%20hypertext%20transfer%20protocol%20web%20services.pdf |
| _version_ | 1848850275168681984 |
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| author | Kakavand, Mohsen Mustapha, Norwati Mustapha, Aida Abdullah, Mohd Taufik Riahi, Hamed |
| author_facet | Kakavand, Mohsen Mustapha, Norwati Mustapha, Aida Abdullah, Mohd Taufik Riahi, Hamed |
| author_sort | Kakavand, Mohsen |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we discuss our review in data mining anomaly detection methods for HTTP web services. Today, many online careers and actions including online shopping and banking are running through web-services. Consequently, the role of Hypertext Transfer Protocol (HTTP) in web services is crucial, since it is the standard facilitator for communication protocol. Hence, among the intruders that bound attacks, HTTP is being considered as a vital middle objective. In the recent years, an effective system that has attracted the attention of the researchers is the anomaly detection which is based on data mining methods. We provided an overview on four general data mining techniques such as classification, clustering, semi-supervised and association rule mining. These data mining anomaly detection methods can be used to computing intelligent HTTP request data, which are necessary in describing user behavior. To meet the challenges of data mining techniques, we provide challenges and issues section for intrusion detection systems in HTTP web services. |
| first_indexed | 2025-11-15T10:03:42Z |
| format | Article |
| id | upm-43614 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:03:42Z |
| publishDate | 2015 |
| publisher | Science Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-436142016-07-22T01:17:34Z http://psasir.upm.edu.my/id/eprint/43614/ A survey of anomaly detection using data mining methods for hypertext transfer protocol web services Kakavand, Mohsen Mustapha, Norwati Mustapha, Aida Abdullah, Mohd Taufik Riahi, Hamed In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we discuss our review in data mining anomaly detection methods for HTTP web services. Today, many online careers and actions including online shopping and banking are running through web-services. Consequently, the role of Hypertext Transfer Protocol (HTTP) in web services is crucial, since it is the standard facilitator for communication protocol. Hence, among the intruders that bound attacks, HTTP is being considered as a vital middle objective. In the recent years, an effective system that has attracted the attention of the researchers is the anomaly detection which is based on data mining methods. We provided an overview on four general data mining techniques such as classification, clustering, semi-supervised and association rule mining. These data mining anomaly detection methods can be used to computing intelligent HTTP request data, which are necessary in describing user behavior. To meet the challenges of data mining techniques, we provide challenges and issues section for intrusion detection systems in HTTP web services. Science Publications 2015 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/43614/1/A%20survey%20of%20anomaly%20detection%20using%20data%20mining%20methods%20for%20hypertext%20transfer%20protocol%20web%20services.pdf Kakavand, Mohsen and Mustapha, Norwati and Mustapha, Aida and Abdullah, Mohd Taufik and Riahi, Hamed (2015) A survey of anomaly detection using data mining methods for hypertext transfer protocol web services. Journal of Computer Science, 11 (1). pp. 89-97. ISSN 1549-3636; ESSN: 1552-6607 http://thescipub.com/PDF/jcssp.2015.89.97.pdf 10.3844/jcssp.2015.89.97 |
| spellingShingle | Kakavand, Mohsen Mustapha, Norwati Mustapha, Aida Abdullah, Mohd Taufik Riahi, Hamed A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title | A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title_full | A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title_fullStr | A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title_full_unstemmed | A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title_short | A survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| title_sort | survey of anomaly detection using data mining methods for hypertext transfer protocol web services |
| url | http://psasir.upm.edu.my/id/eprint/43614/ http://psasir.upm.edu.my/id/eprint/43614/ http://psasir.upm.edu.my/id/eprint/43614/ http://psasir.upm.edu.my/id/eprint/43614/1/A%20survey%20of%20anomaly%20detection%20using%20data%20mining%20methods%20for%20hypertext%20transfer%20protocol%20web%20services.pdf |