蜜罐
计算机科学
时间戳
黑客
服务器
入侵检测系统
云计算
网络安全
端口(电路理论)
方案(数学)
操作系统
计算机安全
工程类
数学
电气工程
数学分析
作者
Stewart Kirubakaran S,V. Ebenezer,P Santhiya,G Manojkumar,S Sophia,Janani A S Snowlin Preethi
标识
DOI:10.1109/icecaa58104.2023.10212345
摘要
For the cloud security or Intrusion Detection System (IDS) a productive scheme for predicting and isolation maintenance is implemented. In this work, the different levels of Honeypots were compared to identify the details of honeypot and its interaction with application in the network. A real time honeypot system is used to detect the attacks. The Hon SSH is a high interaction honeypot that is implemented to gather the information about the hacker who targets the SSH server. The servers were configured using Puppet tool which is an open-source tool used for configuration. The tools like elastic search are used to view the logs collected by the honeypot. The features obtained were like ip-address, timestamp, etc., and best features were noted and stored to analyze the possible attacks and source port. The adoption of revolutionary XGBoost classifier algorithm results in a high rate of accuracy in the prediction of attacks. Finally, the data were analyzed to obtain the performance breakdown.
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