Earticle

초록

영어

The KDD Cup 99 dataset has been the point of attraction for many researchers in the field of intrusion detection from the last decade. Many researchers have contributed their efforts to analyze the dataset by different techniques. Analysis can be used in any type of industry that produces and consumes data, of course that includes security. This paper is an analysis of 10% of KDD cup’99 training dataset based on intrusion detection. We have focused on establishing a relationship between the attack types and the protocol used by the hackers, using clustered data. Analysis of data is performed using k-means clustering; we have used the Oracle 10g data miner as a tool for the analysis of dataset and build 1000 clusters to segment the 494,020 records. The investigation revealed many interesting results about the protocols and attack types preferred by the hackers for intruding the networks.

목차

Abstract
 1. Introduction
  1.1. KDD CUP 99 Data Set
 2. Related Work
 3. Material and Methods
  3.1. Data Collection
  3.2. Process of Data
  3.3. Tools and Techniques
  3.4. Clustering
  3.5. Experimental Analysis
 4. Results and Discussion:
 5. Conclusion
 References

키워드

저자

• Mohammad Khubeb Siddiqui [ College of Computer Engineering and Sciences, Salman bin Abdulaziz University, Kingdom Saudi Arabia ]
• Shams Naahid [ College of Computer Engineering and Sciences, Salman bin Abdulaziz University, Kingdom Saudi Arabia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605