Denial-of-service attack-detection techniques

2006 ◽  
Vol 10 (1) ◽  
pp. 82-89 ◽  
Author(s):  
G. Carl ◽  
G. Kesidis ◽  
R.R. Brooks ◽  
Suresh Rai
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Detection Techniques ◽  
Denial Of Service Attack ◽  
Service Attack

scholarly journals DDOS Attack Detection And Handling Mechanism in WSN

2019 ◽  
Vol 8 (3) ◽  
pp. 4990-4993
Keyword(s):  
Denial Of Service ◽  
Attack Detection ◽  
Sensor Nodes ◽  
Time To Failure ◽  
Detection Techniques ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack ◽  
Ddos Attack Detection ◽  
Mean Time

Wireless sensor network(WSN) uses in many distinct applications including real time event detection. Sensor nodes(SN) have limited energy associated with them that is required to be conserved. Once all the energy of the sensors is drained, then network dies. In addition sensor nodes are exposed to everyone hence SN is susceptible to attacks. Distributed denial of service attack is one of the common attacks caused by malicious attacker causing congestion and decay in lifetime of the network. DDOS attack floods network with the bogus requests. This causes the legitimate request to be avoided by the server due to lack of resources. Detection and prevention of such attacks thus becomes critical. This paper provides study of techniques used to detect DDOS attack along with suggest modification for improving classification accuracy in the detection techniques. in addition this paper also highlight other metrics such as mean time to failure and mean time between failure for improving the detection process.

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

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

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.

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