DDoS flooding attack detection through a step-by-step investigation

2011 ◽  
Author(s):  
Jae-Hyun Jun ◽  
Hyunju Oh ◽  
Sung-Ho Kim
Keyword(s):  
Attack Detection ◽  
Flooding Attack

scholarly journals Design and Implementation of an SNMP-Based Traffic Flooding Attack Detection System

2009 ◽  
Vol 16C (1) ◽  
pp. 13-20 ◽  
Author(s):  
Jun-Sang Park ◽  
Sung-Yun Kim ◽  
Dai-Hee Park ◽  
Mi-Jung Choi ◽  
Myung-Sup Kim
Keyword(s):  
Detection System ◽  
Attack Detection ◽  
Flooding Attack ◽  
Design And Implementation

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.

DDoS flooding attack detection scheme based on F-divergence

2012 ◽  
Vol 35 (11) ◽  
pp. 1380-1391 ◽  
Author(s):  
Hamza Rahmani ◽  
Nabil Sahli ◽  
Farouk Kamoun
Keyword(s):  
Attack Detection ◽  
Detection Scheme ◽  
Flooding Attack

scholarly journals SIP Flooding Attack Detection Using a Trust Model and Statistical Algorithms

2014 ◽  
Vol 22 (2) ◽  
pp. 118-129 ◽  
Author(s):  
Noppawat Chaisamran ◽  
Takeshi Okuda ◽  
Youki Kadobayashi ◽  
Suguru Yamaguchi
Keyword(s):  
Trust Model ◽  
Attack Detection ◽  
Flooding Attack ◽  
Statistical Algorithms

An Intelligent ICMPv6 DDoS Flooding-Attack Detection Framework (v6IIDS) using Back-Propagation Neural Network

2015 ◽  
Vol 33 (3) ◽  
pp. 244-255 ◽  
Author(s):  
Redhwan M. A. Saad ◽  
Mohammed Anbar ◽  
Selvakumar Manickam ◽  
Esraa Alomari
Keyword(s):  
Neural Network ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Attack Detection ◽  
Flooding Attack
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