Filtration Model For DDoS Attack Detection in Real-Time
Filtering traffic of distributed denial of services (DDoS) attack requires extra overhead which mostly results in network performance degradation. This study proposes a filtration model for detecting DDoS attack in real-time without causing negative degradation against network performance. The mode...
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| Format: | Article |
| Language: | English |
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Penerbit UMP
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/9146/ http://umpir.ump.edu.my/id/eprint/9146/ http://umpir.ump.edu.my/id/eprint/9146/1/Filtration%20Model%20For%20DDoS%20Attack%20Detection%20in%20Real-Time.pdf |
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eprints |
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ump-91462018-05-16T07:43:23Z http://umpir.ump.edu.my/id/eprint/9146/ Filtration Model For DDoS Attack Detection in Real-Time Ahmed, Abdulghani Ali QA76 Computer software Filtering traffic of distributed denial of services (DDoS) attack requires extra overhead which mostly results in network performance degradation. This study proposes a filtration model for detecting DDoS attack in real-time without causing negative degradation against network performance. The model investigates network traffic in a scalable way to detect user violations on quality of service regulations. Traffic investigation is triggered only when the network is congested; at that exact moment, burst gateways actually generate an explicit congestion notification to misbehaving users. The misbehaving users are thus further investigated by measuring their consumption ratios of bandwidth. By exceeding the service level agreement bandwidth ratio, user traffic is filtered as malicious traffic. Simulation results demonstrate that the proposed model efficiently monitors malicious traffic and precisely detects DDoS attack. Penerbit UMP 2015 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/9146/1/Filtration%20Model%20For%20DDoS%20Attack%20Detection%20in%20Real-Time.pdf Ahmed, Abdulghani Ali (2015) Filtration Model For DDoS Attack Detection in Real-Time. International Journal of Software Engineering & Computer Sciences (IJSECS), 1. pp. 95-108. ISSN 2289-8522 http://ijsecs.ump.edu.my/images/archive/vol1/08Abdulghani_IJSECS.pdf |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Pahang |
| building |
UMP Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
QA76 Computer software |
| spellingShingle |
QA76 Computer software Ahmed, Abdulghani Ali Filtration Model For DDoS Attack Detection in Real-Time |
| description |
Filtering traffic of distributed denial of services (DDoS) attack requires extra overhead which mostly results in network performance degradation. This study proposes a
filtration model for detecting DDoS attack in real-time without causing negative degradation against network performance. The model investigates network traffic in a
scalable way to detect user violations on quality of service regulations. Traffic investigation is triggered only when the network is congested; at that exact moment,
burst gateways actually generate an explicit congestion notification to misbehaving users. The misbehaving users are thus further investigated by measuring their
consumption ratios of bandwidth. By exceeding the service level agreement bandwidth ratio, user traffic is filtered as malicious traffic. Simulation results demonstrate that the proposed model efficiently monitors malicious traffic and precisely detects DDoS attack. |
| format |
Article |
| author |
Ahmed, Abdulghani Ali |
| author_facet |
Ahmed, Abdulghani Ali |
| author_sort |
Ahmed, Abdulghani Ali |
| title |
Filtration Model For DDoS Attack Detection in Real-Time |
| title_short |
Filtration Model For DDoS Attack Detection in Real-Time |
| title_full |
Filtration Model For DDoS Attack Detection in Real-Time |
| title_fullStr |
Filtration Model For DDoS Attack Detection in Real-Time |
| title_full_unstemmed |
Filtration Model For DDoS Attack Detection in Real-Time |
| title_sort |
filtration model for ddos attack detection in real-time |
| publisher |
Penerbit UMP |
| publishDate |
2015 |
| url |
http://umpir.ump.edu.my/id/eprint/9146/ http://umpir.ump.edu.my/id/eprint/9146/ http://umpir.ump.edu.my/id/eprint/9146/1/Filtration%20Model%20For%20DDoS%20Attack%20Detection%20in%20Real-Time.pdf |
| first_indexed |
2023-09-18T22:07:24Z |
| last_indexed |
2023-09-18T22:07:24Z |
| _version_ |
1777414800613048320 |