Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN)
Joint Authors
Vasupongayya, Sangsuree
Myint Oo, Myo
Kamolphiwong, Sinchai
Kamolphiwong, Thossaporn
Source
Journal of Computer Networks and Communications
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
Software Defined Networking (SDN) has many advantages over a traditional network.
The great advantage of SDN is that the network control is physically separated from forwarding devices.
SDN can solve many security issues of a legacy network.
Nevertheless, SDN has many security vulnerabilities.
The biggest issue of SDN vulnerabilities is Distributed Denial of Service (DDoS) attack.
The DDoS attack on SDN becomes an important problem, and varieties of methods had been applied for detection and mitigation purposes.
The objectives of this paper are to propose a detection method of DDoS attacks by using SDN based technique that will disturb the legitimate user's activities at the minimum and to propose Advanced Support Vector Machine (ASVM) technique as an enhancement of existing Support Vector Machine (SVM) algorithm to detect DDoS attacks.
ASVM technique is a multiclass classification method consisting of three classes.
In this paper, we can successfully detect two types of flooding-based DDoS attacks.
Our detection technique can reduce the training time as well as the testing time by using two key features, namely, the volumetric and the asymmetric features.
We evaluate the results by measuring a false alarm rate, a detection rate, and accuracy.
The detection accuracy of our detection technique is approximately 97% with the fastest training time and testing time.
American Psychological Association (APA)
Myint Oo, Myo& Kamolphiwong, Sinchai& Kamolphiwong, Thossaporn& Vasupongayya, Sangsuree. 2019. Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN). Journal of Computer Networks and Communications،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1172380
Modern Language Association (MLA)
Myint Oo, Myo…[et al.]. Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN). Journal of Computer Networks and Communications No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1172380
American Medical Association (AMA)
Myint Oo, Myo& Kamolphiwong, Sinchai& Kamolphiwong, Thossaporn& Vasupongayya, Sangsuree. Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN). Journal of Computer Networks and Communications. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1172380
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1172380