International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
Volume 123 - Issue 17 |
Published: August 2015 |
Authors: Chaitanya Buragohain, Manash Jyoti Kalita, Santosh Singh, Dhruba K. Bhattacharyya |
![]() |
Chaitanya Buragohain, Manash Jyoti Kalita, Santosh Singh, Dhruba K. Bhattacharyya . Anomaly based DDoS Attack Detection. International Journal of Computer Applications. 123, 17 (August 2015), 35-40. DOI=10.5120/ijca2015905786
@article{ 10.5120/ijca2015905786, author = { Chaitanya Buragohain,Manash Jyoti Kalita,Santosh Singh,Dhruba K. Bhattacharyya }, title = { Anomaly based DDoS Attack Detection }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 123 }, number = { 17 }, pages = { 35-40 }, doi = { 10.5120/ijca2015905786 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Chaitanya Buragohain %A Manash Jyoti Kalita %A Santosh Singh %A Dhruba K. Bhattacharyya %T Anomaly based DDoS Attack Detection%T %J International Journal of Computer Applications %V 123 %N 17 %P 35-40 %R 10.5120/ijca2015905786 %I Foundation of Computer Science (FCS), NY, USA
Distributed denial-of-service (DDoS) attack poses a serious threat to network security. Several methods have been introduced to reduce the damage. However, most of the methods have been found unable to detect the attack in real-time with high detection accuracy. This paper presents a simple yet effective method to detect DDoS attack for all possible attack scenarios given by Mirkoviac [1] viz constant rate, pulsing rate, increasing rate and sub-group. The proposed method is validated using well known CAIDA dataset.