Lupo, James A.
Likarish, Daniel M.
Hart, Douglas I.
College for Professional Studies
MS Information Assurance
School of Computer & Information Science
Thesis - Open Access
Number of Pages
Examining payload content is an important aspect of network security, particularly in today's volatile computing environment. An Intrusion Detection System (IDS) that simply analyzes packet header information cannot adequately secure a network from malicious attacks. The alternative is to perform deep-packet analysis using n-gram language parsing and neural network technology. Self Organizing Map (SOM), PAYL over Self-Organizing Maps for Intrusion Detection (POSEIDON), Anomalous Payload-based Network Intrusion Detection (PAYL), and Anagram are next-generation unsupervised payload anomaly-based IDSs. This study examines the efficacy of each system using the design-science research methodology. A collection of quantitative data and qualitative features exposes their strengths and weaknesses.
Date of Award
© Anthony Mercurio
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Mercurio, Anthony F., "A Critical Analysis of Payload Anomaly-Based Intrusion Detection Systems" (2010). Regis University Student Publications. 363.