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DDoS Attacks Impact on Network Traffic and its Detection Approach

by Anup Bhange, Amber Syad, Satyendra Singh Thakur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 11
Year of Publication: 2012
Authors: Anup Bhange, Amber Syad, Satyendra Singh Thakur
10.5120/5011-7332

Anup Bhange, Amber Syad, Satyendra Singh Thakur . DDoS Attacks Impact on Network Traffic and its Detection Approach. International Journal of Computer Applications. 40, 11 ( December 2012), 36-40. DOI=10.5120/5011-7332

@article{ 10.5120/5011-7332,
author = { Anup Bhange, Amber Syad, Satyendra Singh Thakur },
title = { DDoS Attacks Impact on Network Traffic and its Detection Approach },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 40 },
number = { 11 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 36-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number11/5011-7332/ },
doi = { 10.5120/5011-7332 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:21.510615+05:30
%A Anup Bhange
%A Amber Syad
%A Satyendra Singh Thakur
%T DDoS Attacks Impact on Network Traffic and its Detection Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 11
%P 36-40
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A Denial of Service (DoS) attack is a malicious effort to keep endorsed users of a website or web service from accessing it, or limiting their ability to do so. A Distributed Denial of Service (DDoS) attack is a type of DoS attack in which many computers are used to cripple a web page, website or web-based service. Fault either in users’ implementation of a network or in the standard specification of protocols has resulted in gaps that allow various kinds of network attack to be launched of the type of network attacks, denial-of-service flood attacks have reason the most severe impact. This analysis study on flood attacks and Flash Crowd their improvement, classifying such attacks as either high-rate flood or low-rate flood. Finally, the attacks are appraised against principle related to their characteristics, technique and collision. This paper discusses a statistical approach to analysis the distribution of network traffic to recognize the normal network traffic behavior. The EM algorism is discussed to approximate the distribution parameter of Gaussian mixture distribution model. Another time series analysis method is studied. This paper also discusses a method to recognize anomalies in network traffic, based on a non restricted ?-stable first-order model and statistical hypothesis testing.

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Index Terms

Computer Science
Information Sciences

Keywords

DDoS Impact Anomaly Detection Method ?-Stable Model

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