Synopsis of Security: Using Kerberos Method to Secure File Transfer Sessions

摘要

Secure file transfer sessions in File Transfer Protocol (FTP) is becoming an essential process of prevention and detection the intrusive behaviors nowadays. In this paper, we propose scalable stochastic fingerprints to secure and classify encrypted traffic in File Transfer Protocol (FTP) using Kerberos method instead of Secure Sockets Layers (SSL) method. On the first part, we define Kerberos method and its operational objectives which implemented in the server side of the FTP application. Additionally, we illustrate the strengths of using Kerberos approach and show why it is more efficient than SSL. On the second part, we demonstrate the concept to further improve intrusion detection in FTP by using the machine learning Markov model to evaluate and analyze the Kerberos parameters as its basic model structure having the concept that in a sequence of states. Lastly, we show the effectiveness of the Kerberos technique which results in a very good accuracy of application security.