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논문검색

Botnet Detection Based on Genetic Neural Network

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

저자정보

  • 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

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