alexa An Efficient Attack Resistance Model Using Application
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Research Article

An Efficient Attack Resistance Model Using Application Based Polynomial Distribution

Vince Paul1, Dr. K. Prasadh2, Jasmy Davies3
  1. Research Scholar, Singhania University, Rajasthan, India
  2. Principal, Mookambika Technical Campus, Moovattupuzha, Kerala, India.
  3. Assistant Professor & Research Scholar, Sahrdaya College of Engg. & Tech, Kodakara, Thrissur, Kerala, India
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Abstract

Due to the increasing threat to the Internet on both popular Internet sites and Internet infrastructure, it is very challenging to provide reliable data transfer in a more secured manner for time-critical applications in an energyefficient way. Several attack resistance schemes have been proposed to increase the effect of detection rate and the limitations of security, minimize the power overload, and energy consumption. However, they all disregard the time factor they take to accomplish the task of providing security and therefore miss significant opportunities for attack resistance. In this paper, we propose new approach called as the Application based Polynomial Distribution (A-PD) model for mitigating the problems related to application oriented DDOS attack. With carefully designed attack resistance strategies, A-PD model distributes the application services prior to sending the packet data streams. Since the distribution of packet data streams is performed in an efficient manner, the abnormality of service or the attack rate is minimized. The organization of packet data stream is performed using polynomial distribution according to the classification of application services using probability density function. The application of probability density function increases the detection rate and accordingly equate with the network traffic. Our techniques significantly outperform the state-of-the-art works. In comparison to prior work, our experimental results show that our model outperforms better in terms of detection rate, execution time, minimizing load overhead achieve. This, in turn, leads to improved security

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