Unsupervised learning with hierarchical feature selection for DDoS mitigation within the ISP domain

被引:8
作者
Ko, Ili [1 ]
Chambers, Desmond [1 ]
Barrett, Enda [1 ]
机构
[1] Natl Univ Ireland, Galway, Ireland
关键词
ANN; artificial neural network; cyber security; DDoS mitigation; feature selection; self-organizing map; unsupervised learning; ATTACKS;
D O I
10.4218/etrij.2019-0109
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A new Mirai variant found recently was equipped with a dynamic update ability, which increases the level of difficulty for DDoS mitigation. Continuous development of 5G technology and an increasing number of Internet of Things (IoT) devices connected to the network pose serious threats to cyber security. Therefore, researchers have tried to develop better DDoS mitigation systems. However, the majority of the existing models provide centralized solutions either by deploying the system with additional servers at the host site, on the cloud, or at third party locations, which may cause latency. Since Internet service providers (ISP) are links between the internet and users, deploying the defense system within the ISP domain is the panacea for delivering an efficient solution. To cope with the dynamic nature of the new DDoS attacks, we utilized an unsupervised artificial neural network to develop a hierarchical two-layered self-organizing map equipped with a twofold feature selection for DDoS mitigation within the ISP domain.
引用
收藏
页码:574 / 584
页数:11
相关论文
共 36 条
[1]  
Aburomman AA, 2016, 2016 INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL, ELECTRONIC AND SYSTEMS ENGINEERING (ICAEES), P362, DOI 10.1109/ICAEES.2016.7888070
[2]  
[Anonymous], 2017, ABS171106041 CORR
[3]  
[Anonymous], 2018, Q SECURITY REPORTS G
[4]  
[Anonymous], 2018, MIR BOTN
[5]  
[Anonymous], 2011, INT J COMPUT APPL
[6]  
Bocek T, 2017, ERCIM NEWS, P14
[7]  
Choksi K., 2014, INTRUSION DETECTION
[8]  
Fernando ZT, 2014, 2014 FIRST INTERNATIONAL CONFERENCE ON NETWORKS & SOFT COMPUTING (ICNSC), P162, DOI 10.1109/CNSC.2014.6906666
[9]  
Fitriani S, 2016, 2016 ASIA PACIFIC CONFERENCE ON MULTIMEDIA AND BROADCASTING (APMEDIACAST), P36, DOI 10.1109/APMediaCast.2016.7878168
[10]   Exponential smoothing: The state of the art - Part II [J].
Gardner, Everette S., Jr. .
INTERNATIONAL JOURNAL OF FORECASTING, 2006, 22 (04) :637-666