Earticle

초록

영어

Tools required for the security purposes are firewall, passwords, IDS, IPS for the detection of anomaly and prevent it from sending out the harmful traffic to the network. So, it is very necessary to examine the behavior of traffic that coming to the network and recognize the anomalous behavior. In this paper, statistical based chi-square method is used to detect the anomalous behavior and predict the intrusions by calculating the observed and expected frequencies. Setting of interval is difficult for the detection of anomaly but in our case we set interval according to the less variation in traffic. Traffic contains from the backscatter dataset. Chi-square method is good to detect the anomalous behaviors because it gives the Poisson’s distribution for the whole traffic on network. Large difference shows anomaly occurs.

목차

Abstract
 1. Introduction
 2. Technique Used
  2.1. Statistical Approach
  2.2. Data Mining Approach
  2.3. Machine Learning
  2.4. Knowledge Approach
 3. Related Work
 4. Proposed Work
  4.1. Chi-square (X2)
  4.2. Material
  4.3. Methodology
 5. Results and Discussion
 6. Conclusion
 References

키워드

저자

• Sheenam [ Research scholar, Dept. of Computer science and Engineering ]
• Abhinav Bhandari [ Assitant Professor, Punjabi university, Patiala ]

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