Voting extreme learning machine based distributed denial of service attack detection in cloud computing

2020 ◽  
Vol 53 ◽  
pp. 102532 ◽  
Author(s):  
Gopal Singh Kushwah ◽  
Virender Ranga
2019 ◽  
Vol 20 (2) ◽  
pp. 285-298 ◽  
Author(s):  
A. Dhanapal ◽  
P. Nithyanandam

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.


2020 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Bibek Naha ◽  
Siddhartha Banerjee ◽  
Sayanti Mondal

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.


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

Cloud services among public and business companies have become popular in recent years. For production activities, many companies rely on cloud technology. Distributed Denial of Services (DDoS) attack is an extremely damaging general and critical type of cloud attacks. Several efforts have been made in recent years to identify numerous types of DDoS attacks. This paper discusses the different types of DDoS attacks and their cloud computing consequences. Distributed Denial of Service attack (DDoS) is a malicious attempt to disrupt the normal movement of a targeted server, service or network through influx of internet traffic overwhelming the target or its infrastructure. The use of multiple affected computer systems as a source of attacks makes DDoS attacks effective. Computers and other networked tools, including IoT phones, may be included on exploited machines. A DDoS attack from a high level resembles a traffic jam that is caused by roads that prevents normal travel at their desired destination. So DDoS Attack is a major challenging problem in integrated Cloud and IoT. Hence, this paper proposes Shield Advanced Mitigation System of Distributed Denial of Service Attack in the integration of Internet of Things and Cloud Computing Environment. This secure architecture use two verification process to identify whether user is legitimate or malicious. Dynamic Captcha Testing with Equal Probability test for first verification process, moreover Zigsaw Image Puzzle Test is used for second verification process, and Intrusion Detection Prevention System is used to identify and prevent malicious user, moreover reverse proxy is used to hide server location. These functional components and flow could strengthen security in Client side network to provide cloud services furthermore to overcome distributed denial of service attack in the integration of Internet of Things and Cloud Environment.


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