DoSTDM: A denial of service detection model using firewall data traffic pattern matching
This research deals with Denial of Service (DoS) flooding attacks. These types of attacks toward internet connected networks are on the rise. The research proposes a model that triangulate between statistical and neural network forecasting approaches. The proposed model can identify DoS attacks usin...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Curtin University
2013
|
| Online Access: | http://hdl.handle.net/20.500.11937/1683 |
| _version_ | 1848743738326646784 |
|---|---|
| author | Ahmad Salem, Mohammed Ali Mohammed |
| author_facet | Ahmad Salem, Mohammed Ali Mohammed |
| author_sort | Ahmad Salem, Mohammed Ali Mohammed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This research deals with Denial of Service (DoS) flooding attacks. These types of attacks toward internet connected networks are on the rise. The research proposes a model that triangulate between statistical and neural network forecasting approaches. The proposed model can identify DoS attacks using the firewall rejected traffic falling outside the normal levels that could indicate a DoS attack. The triangulation approach provided the research model with multi prediction techniques with high accuracy. |
| first_indexed | 2025-11-14T05:50:20Z |
| format | Thesis |
| id | curtin-20.500.11937-1683 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T05:50:20Z |
| publishDate | 2013 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-16832017-02-20T06:38:23Z DoSTDM: A denial of service detection model using firewall data traffic pattern matching Ahmad Salem, Mohammed Ali Mohammed This research deals with Denial of Service (DoS) flooding attacks. These types of attacks toward internet connected networks are on the rise. The research proposes a model that triangulate between statistical and neural network forecasting approaches. The proposed model can identify DoS attacks using the firewall rejected traffic falling outside the normal levels that could indicate a DoS attack. The triangulation approach provided the research model with multi prediction techniques with high accuracy. 2013 Thesis http://hdl.handle.net/20.500.11937/1683 en Curtin University fulltext |
| spellingShingle | Ahmad Salem, Mohammed Ali Mohammed DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title | DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title_full | DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title_fullStr | DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title_full_unstemmed | DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title_short | DoSTDM: A denial of service detection model using firewall data traffic pattern matching |
| title_sort | dostdm: a denial of service detection model using firewall data traffic pattern matching |
| url | http://hdl.handle.net/20.500.11937/1683 |