Entropy-based denial-of-service attack detection in cloud data center

2015 ◽  
Vol 27 (18) ◽  
pp. 5623-5639 ◽  
Author(s):  
Jiuxin Cao ◽  
Bin Yu ◽  
Fang Dong ◽  
Xiangying Zhu ◽  
Shuai Xu
Keyword(s):  
Data Center ◽  
Denial Of Service ◽  
Attack Detection ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Denial Of Service Attack ◽  
Service Attack

Low rate TCP denial-of-service attack detection at edge routers

2005 ◽  
Vol 9 (4) ◽  
pp. 363-365 ◽  
Author(s):  
A. Shevtekar ◽  
K. Anantharam ◽  
N. Ansari
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Low Rate

The HTTP Flooding Attack Detection to Secure and Safeguard Online Applications in the Cloud

2019 ◽  
Vol 10 (3) ◽  
pp. 41-58
Author(s):  
Dhanapal A ◽  
Nithyanandam P
Keyword(s):  
Linear Prediction ◽  
Denial Of Service ◽  
Attack Detection ◽  
Healthcare Applications ◽  
Normal Behaviour ◽  
Data Set ◽  
Denial Of Service Attack ◽  
Flooding Attack ◽  
Cloud Properties ◽  
Service Attack

Cloud computing is the cutting edge and has become inevitable in all forms of computing. This is due to its nature of elasticity, cost-effectiveness, availability, etc. The online applications like e-commerce, and e-healthcare applications are moving to the cloud to reduce their operational cost. These applications have the vulnerability of a HTTP flooding Distributed Denial of Service attack in the cloud. This flooding attack aims to overload the application, making it unable to process genuine requests and bring it down. So, these applications need to be secured and safeguarded against such attacks. This HTTP flooding attack is one of the key challenging issues as it shows normal behaviour with regard to all lower networking layers like TCP 3-way handshaking by mimicking genuine requests and it is even harder in the cloud due to the cloud properties. This article offers a solution for detecting a HTTP flooding attack in the cloud by using the novel TriZonal Linear Prediction (TLP) model. The solution was implemented using OpenStack and the FIFA Worldcup '98 data set for experimentation.

scholarly journals Noise-Robust Multilayer Perceptron Architecture for Distributed Denial of Service Attack Detection

2020 ◽  
pp. 1-1
Author(s):  
Joao Paulo A. Maranhao ◽  
Joao Paulo C. L. da Costa ◽  
Edison Pignaton de Freitas ◽  
Elnaz Javidi ◽  
Rafael T. de Sousa
Keyword(s):  
Multilayer Perceptron ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Noise Robust
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