Earticle

초록

영어

Botnet have turned into the most serious security dangers on the present Internet framework. A botnet is most extensive and regularly happens in today's cyber-attacks, bringing about the serious risk of our system resources and association's properties. Botnets are accumulations of compromised computers (Bots) which are remotely regulated by its creator (BotMaster) under a typical Command-and-Control (C&C) framework. Botnets cannot just be implemented utilizing existing well-known applications and additionally developed by unknown or inventive applications. This makes the botnet detection a challenging issue. In this paper proposed an anomaly detection model based on genetic neural network system, which joined the significant global searching capability of genetic algorithm with the precise local searching element of back propagation feed forward neural networks to improve the initial weights of neural network.

목차

Abstract
 1. Introduction
 2. Introduce BP Feed Forward Neural Network and Genetic Algorithm
 3. Briefs about Combination of ANN-GA for Detection of a Botnet
 4. The Entire GNN is Explained as the Following
 5. Feature Selection for Botnet Detection
 6. Performance of the Proposed Model
 7. Conclusions and Future Work
 References

키워드

저자

• Chunyong Yin [ Jiangsu Key Laboratory of Meteorological Observation and Information ]
• Ardalan Husin Awlla [ Jiangsu Key Laboratory of Meteorological Observation and Information ]
• Zhichao Yin [ Processing, School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Jin Wang [ Jiangsu Key Laboratory of Meteorological Observation and Information ]

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