Different approaches for the detection of SSH anomalous connections

The Secure Shell Protocol (SSH) is a well-known standard protocol, mainly used for remotely accessing shell accounts on Unix-like operating systems to perform administrative tasks. As a result, the SSH service has been an appealing target for attackers, aiming to guess root passwords performing dictionary attacks or to directly exploit the service itself. To identify such situations, this article addresses the detection of SSH anomalous connections from an intrusion detection perspective. The main idea is to compare several strategies and approaches for a better detection of SSH-based attacks. To test the classification performance of different classifiers and combinations of them, SSH data coming from a real-world honeynet are gathered and analysed. For comparison purposes and to draw conclusions about data collection, both packet-based and flow data are analysed. A wide range of classifiers and ensembles are applied to these data, as well as different validation schemes for better analysis of the obtained results. The high-rate classification results lead to positive conclusions about the identification of malicious SSH connections

Different approaches for the detection of SSH anomalous connections

Abstract The Secure Shell Protocol (SSH) is a well-known standard protocol, mainly used for remotely accessing shell accounts on Unix-like operating systems to perform administrative tasks. As a result, the SSH service has been an appealing target for attackers, aiming to guess root passwords performing dictionary attacks or to directly exploit the service itself. To identify such situations, this article addresses the detection of SSH anomalous connections from an intrusion detection perspective. The main idea is to compare several strategies and approaches for a better detection of SSH-based attacks. To test the classification performance of different classifiers and combinations of them, SSH data coming from a real-world honeynet are gathered and analysed. For comparison purposes and to draw conclusions about data collection, both packet-based and flow data are analysed. A wide range of classifiers and ensembles are applied to these data, as well as different validation schemes for better analysis of the obtained results. The high-rate classification results lead to positive conclusions about the identification of malicious SSH connections

Classification of SSH Anomalous Connections

The Secure Shell Protocol (SSH) is a well-known standard protocol for remote login and used as well for other secure network services over an insecure network. It is mainly used for remotely accessing shell accounts on Unix-liked operating systems to perform administrative tasks. For this reason, the SSH service has been for years an attractive target for attackers, aiming to guess root passwords performing dictionary attacks, or to directly exploit the service itself. To test the classification performance of different classifiers and combinations of them, this study gathers and analyze SSH data coming from a honeynet and then it is analysed by means of a wide range of classifiers. The high-rate classification results lead to positive conclusions about the identification of malicious SSH connections