Earticle

초록

영어

With the development of the networks, the security of computer networks is becoming more and more serious. The information openness, sharing and interconnection are three important characteristics of computer networks. However, the amounts of intruders and attackers have been grows with the popularization of computers. Therefore, the focus of network security is preventing systems from being invaded effectively. Intrusion detection as a key technology of network security active defense system is designed to distinguish normal behaviors and attack behaviors. Intrusion detection is divided into misuse detection and anomaly detection, and using clustering algorithm is one of the most effective methods for anomaly detection. In this paper, a clustering algorithm based on fast search and find of density peaks is used to distinguish the normal and abnormal network connections to achieve the purpose of anomaly detection. The performance of the algorithm is tested by a data set selected from KDD CUP99. Experiment results show that this algorithm is more suitable than the traditional K-means in data sets containing a large amount of data and uneven density distribution.

목차

Abstract
 1. Introduction
 2. Application of Clustering Analysis in Network Intrusion Detection
 3. Researches on Clustering Algorithm
 4. A Clustering Algorithm using in Anomaly Detection
  4.1. Clustering by Fast Search-and-Find of Density Peaks
  4.2. Comparison and Analysis
 5. Experiment and Result Analysis
  5.1. The First Experiment
  5.2. The Second Experiment
 6. Conclusions
 References

키워드

저자

• Chunyong Yin [ School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Sun Zhang [ School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Zhichao Yin [ Nanjing No.1 Middle School, Nanjing, Jiangsu, Postal code 210001, China ]
• Jin Wang [ School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China ]

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