Browsing by Author "Ratti, Ritesh"

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    Application Specific NIDS (using unsupervised techniques)
    (2024) Ratti, Ritesh
    In recent years, the use of unsupervised learning-based methods for network intrusion detection has attracted much attention. Multiple methods using unsupervised mechanisms have been proposed that utilize the information in various formats like network packets, flow information, etc., and use various methods for attack identification. Most of these methods have the limitations on not considering the time factor inherently but explicitly using the time-dependent features for various time windows and considering equal importance for all previous contexts. Also ignoring the fact that each protocol-specific attack is unique and ignoring the protocol awareness to determine attacks. Moreover, considering a single type of view or set of features (network header or flow) to build a machine learning model and ignoring the importance of different views in attack determination. This thesis presents four unsupervised learning-based methods in this direction.