Distributed Denial of Service Attack Detection Using Ant Bee Colony and Artificial Neural Network in Cloud Computing

2017 ◽  
pp. 165-175
Author(s):  
Uzma Ali ◽  
Kranti K. Dewangan ◽  
Deepak K. Dewangan
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Cloud Computing ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Denial Of Service Attack ◽  
Bee Colony ◽  
Service Attack ◽  
Artificial Neural

scholarly journals The Slow HTTP Distributed Denial of Service Attack Detection in Cloud

2019 ◽  
Vol 20 (2) ◽  
pp. 285-298 ◽  
Author(s):  
A. Dhanapal ◽  
P. Nithyanandam
Keyword(s):  
Cloud Computing ◽  
Financial Services ◽  
Denial Of Service ◽  
Attack Detection ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Denial Of Service Attack ◽  
Ddos Attack ◽  
Service Attack ◽  
The Cost

Cloud computing became popular due to nature as it provides the flexibility to add or remove the resources on-demand basis. This also reduces the cost of investments for the enterprises significantly. The adoption of cloud computing is very high for enterprises running their online applications. The availability of online services is critical for businesses like financial services, e-commerce applications, etc. Though cloud provides availability, still these applications are having potential threats of going down due to the slow HTTP Distributed Denial of Service (DDoS) attack in the cloud. The slow HTTP attacks intention is to consume all the available server resources and make it unavailable to the real users. The slow HTTP DDoS attack comes with different formats such as slow HTTP headers attacks, slow HTTP body attacks and slow HTTP read attacks. Detecting the slow HTTP DDoS attacks in the cloud is very crucial to safeguard online cloud applications. This is a very interesting and challenging topic in DDoS as it mimics the slow network. This paper proposed a novel method to detect slow HTTP DDoS attacks in the cloud. The solution is implemented using the OpenStack cloud platform. The experiments conducted exhibits the accurate results on detecting the attacks at the early stages. The slowHTTPTest open source tool is used in this experiment to originate slow HTTP DDoS attacks.

A SURVEY ON CLOUD-DENIAL OF SERVICE

2020 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Bibek Naha ◽  
Siddhartha Banerjee ◽  
Sayanti Mondal
Keyword(s):  
Cloud Computing ◽  
Comparative Study ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Cloud Environment ◽  
Dos Attack ◽  
Huge Amount ◽  
Denial Of Service Attack ◽  
Service Attack ◽  
Insight Into

Cloud Computing is one of the most nurtured as well as debated topic in today’s world. Billions of data of various fields ranging from personal users to large business enterprises reside in Cloud. Therefore, availability of this huge amount of data and services is of immense importance. The DOS (Denial of Service) attack is a well-known threat to the availability of data in a smaller premise. Whenever, it’s a Cloud environment this simple DOS attack takes the form of DDOS (Distributed Denial of Service) attack. This paper provides a generic insight into the various kinds of DOS as well as DDOS attacks. Moreover, a handful of countermeasures have also been depicted here. In a nutshell, it aims at raising an awareness by outlining a clear picture of the Cloud availability issues.Our paper gives a comparative study of different techniques of detecting DOS.

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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