Methodologies to prevent DDOS Attacks using Clustering algorithm during Peak Hours of Server – Probabilistic Packet Marking (PPM)

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-41 Number-1
Year of Publication : 2016
Authors : M.Padmavathy, Dr. M. Ramakrishnan
  10.14445/22312803/IJCTT-V41P102

MLA

M.Padmavathy, Dr. M. Ramakrishnan "Methodologies to prevent DDOS Attacks using Clustering algorithm during Peak Hours of Server – Probabilistic Packet Marking (PPM)". International Journal of Computer Trends and Technology (IJCTT) V41(1):10-15, November 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In the tremendous growth of internet world, networking communications play an important role. Network communication is one of the sharing of information between server and clients. But in today fast technology, the number of clients has increased and consequently the server is unable to send the response to all the legitimate clients in time. It may also happen due to the attack of intruders. So the prevention of this kind of attacks is the important aspect throughout the network communication. Specifically, unsupervised data mining clustering techniques allow to effectively distinguishing the normal traffic from malicious traffic in a good accuracy. In this paper, a bird view for a set of probabilistic packet marking methodologies has been discussed to prevent the DDOS attacks using clustering algorithm during peak hours of server. These various methodologies are useful to find the IP address of clients and find the intruders among them depending upon the client’s behavior. And also we envision DDoS attack starts when network traffic is more than our default threshold. In this type of packet marking protocol, packets are marked based on predefined probability.

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Keywords
Server, DDOS attacks, Intruders, Probabilistic Packet Marking (PPM), Clustering, Peak hours.