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Showing 1 to 3 of 3 for “"N-gram analysis"”.
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Detection of malicious content in JSON structured data using multiple concurrent anomaly detection methods
… algorithm. Metrics such as Shannon entropy, n-gram analysis, JSON structure similarity, character string length, and JSON attribute values are utilized. A goal of this research was the detection of attacks at a rate at least better than chance expectation. This goal was met and exceeded as …
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Improving Companion AI Behavior in MimicA
… MimicA framework by adding feature selection, n-gram analysis, an improved feedback system, random forest classifier, and a new system for picking a location for actions. In addition, we refactored and updated the original framework to make it easier to use for game developers and the game, Lord …
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Machine Learning Interpretability in Malware Detection
… and server-side polymorphism. Further, new programming paradigms such as fileless malware, that is malware that exist only in the main memory (RAM) of the infected host, add to the challenges faced with modern day malware detection. This has led security specialists to turn to machine learning …