Distributed Denial of Service (DDoS) is a type of attack in the application layer initiated from the various hosts to a single web server. The aim of this attack is to consume all the resources of the targeted system by exploiting the vulnerability. We proposed a mathematical model called Recurrence Quantification Analysis (RQA) for detecting the DDoS attacks by computing entropy and determinism of selected packet attributes. To detect the anomalies and check the performance we considered the live traffic traces from the network and various RQA parameters like entropy, laminarity and determinism were used to determine the uncertainty or randomness in the dataset.

Jeyanthi N

Department of Software and Systems Engineering

School of Information Technology and Engineering

Vellore Campus

Thandeeswaran R

Department of Digital Communications

Vinithra J

Iyengar N.C.S.N.

Ananya

Akash

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

A Recurrence Quantification Analytical Approach to Detect DDoS Attacks

2011 International Conference on Computational Intelligence and Communication Networks

Security in this world of digital computing plays a typical role, since all the operations are automated and large volumes of data are being maintained in the servers. Cloud computing is one of the evolving technologies where a huge volume of storage is made on-line, data and services are also distributed. Because of its distributed nature, they have become easy targets for the intruders to exploit the information. The well known Distributed Denial of Service (DDoS) attack is the most prominent attacks in this area of computing. DDoS is the single largest threat to internet and internet of things. This paper provides a wide survey on various DDoS attacks, their vulnerabilities and countermeasures proposed against them. Also this paper provides an in-depth analysis on effects of DDoS attacks in the Cloud environment. Through the analysis done it will be useful for designing a secured cloud infrastructure which will abide the DDoS attacks. © 2014 IEEE.

The 2014 International Symposium on Networks, Computers and Communications

Distributed Denial of service attacks and its effects on Cloud environment- a survey

Fulltext

International Journal of Grid and Utility Computing

A multilevel thrust filtration defending mechanism against DDoS attacks in cloud computing environment

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.

Journal	Data powered by Typeset2011 International Conference on Computational Intelligence and Communication Networks
Publisher	Data powered by TypesetIEEE
Open Access	No