Earticle

초록

영어

Today the scale, complexity and intensity of Denial of Service attacks has increased many folds. These attacks have moved from simple flooding based attacks to sophisticated Application based attacks as well as Protocol specific attacks.The challenge is to develop detection algorithms that can distinguish between the attacks like the new pulsating denial of service and legitimate traffic like Flash events. The presence of self-similarity in computer network traffic has introduced a newer dimension in techniques being developed for anomaly detection in aggregated network traffic.We propose use of wavelets to distinguish between legitimate flash events and pulsating distributed denial of service attacks and generating images to show point-of-presence of the attack.The detection methodology has also been tested on KDD Dataset.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Theoretical Background
 4. Detection Methodology
  4.1. Detection and Characterization of the attacks
 5. Simulation Model
  5.1. Clients
  5.2. Server
 6. Experiments, Results & Discussions
  6.1. Pre Test Experiments
  6.2. Hypothesis Testing:
 7. Validation based on KDD Dataset
  7.1. KDD Dataset
  7.2. Results
 8. Conclusion
 References

키워드

저자

• Gagandeep Kaur [ Jaypee Institute of Information Technology, Noida, UP, India ]
• Vikas Saxena [ Jaypee Institute of Information Technology, Noida, UP, India ]
• J. P. Gupta [ Sharda University, Noida, UP, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605