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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek
Superb: Superior Behavior-Based Anomaly Detection Defining Authorized Users' Traffic Patterns, Daniel Karasek
Master of Science in Computer Science Theses
Network anomalies are correlated to activities that deviate from regular behavior patterns in a network, and they are undetectable until their actions are defined as malicious. Current work in network anomaly detection includes network-based and host-based intrusion detection systems. However, network anomaly detection schemes can suffer from high false detection rates due to the base rate fallacy. When the detection rate is less than the false positive rate, which is found in network anomaly detection schemes working with live data, a high false detection rate can occur. To overcome such a drawback, this paper proposes a superior behavior-based anomaly detection …
Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Malware Image Classification Using Machine Learning With Local Binary Pattern, Jhu-Sin Luo, Dan Lo
Master of Science in Computer Science Theses
Malware classification is a critical part in the cybersecurity.
Traditional methodologies for the malware classification
typically use static analysis and dynamic analysis to identify malware.
In this paper, a malware classification methodology based
on its binary image and extracting local binary pattern (LBP)
features are proposed. First, malware images are reorganized into
3 by 3 grids which is mainly used to extract LBP feature. Second,
the LBP is implemented on the malware images to extract features
in that it is useful in pattern or texture classification. Finally,
Tensorflow, a library for machine learning, is applied to classify
malware images with …