Application of Artificial Neural Network in Detection of Probing Attacks
A solo attack may cause a big loss in computer and network systems, its prevention is, therefore, very inevitable. Precise detection is very important to prevent such losses. Such detection is a pivotal part of any security tools like intrusion detection system, intrusion prevention system, and...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2010
|
| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/708/ http://scholars.utp.edu.my/id/eprint/708/1/ACM-ahmadeprinted.pdf |
| _version_ | 1848659028287160320 |
|---|---|
| author | I., Ahmad Azween, Abdullah Alghamdi, Abdullah |
| author_facet | I., Ahmad Azween, Abdullah Alghamdi, Abdullah |
| author_sort | I., Ahmad |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | A solo attack may cause a big loss in computer and network
systems, its prevention is, therefore, very inevitable. Precise
detection is very important to prevent such losses. Such detection is
a pivotal part of any security tools like intrusion detection system,
intrusion prevention system, and firewalls etc. Therefore, an
approach is provided in this paper to analyze denial of service attack
by using a supervised neural network. The methodology used
sampled data from Kddcup99 dataset, an attack database that is a
standard for judgment of attack detection tools. The system uses
multiple layered perceptron architecture and resilient
backpropagation for its training and testing. The developed system
is then applied to denial of service attacks. Moreover, its
performance is also compared to other neural network approaches
which results more accuracy and precision in detection rate |
| first_indexed | 2025-11-13T07:23:55Z |
| format | Conference or Workshop Item |
| id | oai:scholars.utp.edu.my:708 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:23:55Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:7082017-01-19T08:24:44Z http://scholars.utp.edu.my/id/eprint/708/ Application of Artificial Neural Network in Detection of Probing Attacks I., Ahmad Azween, Abdullah Alghamdi, Abdullah QA75 Electronic computers. Computer science A solo attack may cause a big loss in computer and network systems, its prevention is, therefore, very inevitable. Precise detection is very important to prevent such losses. Such detection is a pivotal part of any security tools like intrusion detection system, intrusion prevention system, and firewalls etc. Therefore, an approach is provided in this paper to analyze denial of service attack by using a supervised neural network. The methodology used sampled data from Kddcup99 dataset, an attack database that is a standard for judgment of attack detection tools. The system uses multiple layered perceptron architecture and resilient backpropagation for its training and testing. The developed system is then applied to denial of service attacks. Moreover, its performance is also compared to other neural network approaches which results more accuracy and precision in detection rate 2010 Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/708/1/ACM-ahmadeprinted.pdf I., Ahmad and Azween, Abdullah and Alghamdi, Abdullah (2010) Application of Artificial Neural Network in Detection of Probing Attacks. In: IEEE symposium on industrial electronics and applications. |
| spellingShingle | QA75 Electronic computers. Computer science I., Ahmad Azween, Abdullah Alghamdi, Abdullah Application of Artificial Neural Network in Detection of Probing Attacks |
| title | Application of Artificial Neural Network in Detection of Probing Attacks |
| title_full | Application of Artificial Neural Network in Detection of Probing Attacks |
| title_fullStr | Application of Artificial Neural Network in Detection of Probing Attacks |
| title_full_unstemmed | Application of Artificial Neural Network in Detection of Probing Attacks |
| title_short | Application of Artificial Neural Network in Detection of Probing Attacks |
| title_sort | application of artificial neural network in detection of probing attacks |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/708/ http://scholars.utp.edu.my/id/eprint/708/1/ACM-ahmadeprinted.pdf |